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Dr. George A. KomatsoulisOncology is a fertile field for the development of what the Institute of Medicine terms a “Rapid Learning Health System.” To this end, the American Society of Clinical Oncology (ASCO) created CancerLinQ, a system designed to enable a virtuous cycle in which research drives care and data from routine care helps to inform the next generation of treatment standards and research questions. CancerLinQ is a community of oncology practices that have joined together in this goal, as well as a specific technology platform that enables the collection, aggregation and harmonization of data from Electronic Health Record (EHR) systems for the purpose of improving quality of care for patients. Methods used to extract, process and manage data in CancerLinQ, as well as general properties of the CancerLinQ data sets will be discussed.

Session details...

 

BIO:

George A. Komatsoulis, Ph.D. is Chief of Bioinformatics at CancerLinQ, a Rapid Learning Health System project at the American Society of Clinical Oncology (ASCO). Dr. Komatsoulis has been working in bioinformatics for more than 30 years across academia, government, industry and the non-profit sector focusing on data harmonization and interoperability. His prior experience includes Human Genome Sciences, Inc. and the National Institutes of Health where he worked at the National Cancer Institute, the National Center for Biotechnology Information and the Office of the NIH Associate Director for Data Science. At the NCI, Dr. Komatsoulis held a number of positions including Deputy Director and Director (acting) of the Center for Biomedical Informatics and Information Technology (CBIIT), as well as acting as Chief Information Officer during the development of the NCI Shady Grove campus. Dr. Komatsoulis is known for developing the NCI Cancer Genomics Cloud Pilots and the NIH Commons Credits program. He has a B.S. in Microbiology from Cornell University and a Ph.D. in Molecular Biology and Biochemistry from the California Institute of Technology. 

SUMMARY:

Topic:  Development of an Aggregated Data Set from Multiple Electronic Health Record (EHR) Systems to Support Improved Quality of Oncology Practice

Speaker: George Komatsoulis, Ph.D. 

Date: Wednesday, February 28, 2018

Time: 11 AM – 12 PM ET

Room: TE110

You are invited to listen to Dr. Komatsoulis's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Komatsoulis will present on site at the Shady Grove building.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. George HripcsakThe Observational Health Data Sciences and Informatics (OHDSI) network has mapped data from more than 50 databases (that contain information on more than 400 million patients) to the OMOP common data model and it uses an open science approach to conduct distributed research. It has analyzed data from 11 databases (containing information on more than 250 million patient records) to ascertain the sequence of treatments over three years in patients with depression, diabetes or hypertension.  This presentation will describe how electronic health records and claims data can be used to ascertain treatments received by cancer patients; present data on the sequence of treatments for cancer patients with depression, diabetes or hypertension, and the accuracy of cancer care documentation; and discuss approaches to improve abstraction of cancer information from electronic health records.

Session details...

 

BIOS:

George Hripcsak, M.D., M.S., is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for NewYork-Presbyterian Hospital. Dr. Hripcsak is a board-certified internist with degrees in chemistry, medicine, and biostatistics. He led the effort to create the Arden Syntax, a language for representing health knowledge that has become a national standard. Dr. Hripcsak’s current research focus is on the clinical information stored in electronic health records and on the development of next-generation health record systems. Using nonlinear time series analysis, machine learning, knowledge engineering, and natural language processing, he is developing the methods necessary to support clinical research and patient safety initiatives. As Director of Medical Informatics Services, he oversees a 12,000-user, 4-million-patient clinical information system and data repository. He co-chaired the Meaningful Use Workgroup of the U.S. Department of Health and Human Services’ Office of the National Coordinator of Health Information Technology; it defines the criteria by which health care providers collect incentives for using electronic health records. Dr. Hripcsak was elected fellow of the American College of Medical Informatics in 1995 and served on the Board of Directors of the American Medical Informatics Association (AMIA). As chair of the AMIA Standards Committee, he coordinated the medical-informatics community response to the U.S. Department of Health and Human Services for the health-informatics standards rules under the Health Insurance Portability and Accountability Act of 1996. Dr. Hripcsak chaired the U.S. National Library of Medicine’s Biomedical Library and Informatics Review Committee, and he is a fellow of the National Academy of Medicine, the American College of Medical Informatics, and the New York Academy of Medicine. He has served on several National Academy of Medicine and National Academy of Sciences committees, and he has published over 250 papers.

Gurvaneet Randhawa, M.D., M.P.H., is a Medical Officer in the Health Systems and Interventions Research Branch (HSIRB). Before joining NCI, he worked at the AHRQ for 13 years where he was a Medical Officer and a Senior Advisor on Clinical Genomics and Personalized Medicine. Prior to joining AHRQ, he completed his Preventive Medicine residency at Johns Hopkins University in 2002, which included a stint at NIAID. He completed an Internal Medicine internship at the University of Pennsylvania in 2000. Prior to that, he trained for nine years in biomedical research at Johns Hopkins and at M.D. Anderson Cancer Center. His research interests at that time were in molecular biology and genomics with a focus on chronic myelogenous leukemia. He obtained his medical degree from Medical College, Amritsar, India.

Dr. Randhawa served in several roles at AHRQ. He started work in the U.S. Preventive Services Task Force (USPSTF) program and soon became the USPSTF program director. He led a reengineering effort to increase program efficiency and productivity, which cleared a multi-year backlog of USPSTF recommendations. More recently, he was the lead author of four ARRA-funded RFAs that created four new programs: Prospective Outcome Systems using Patient-specific Electronic data to Compare Tests and therapies (PROSPECT); scalable distributed research networks; enhanced registries for quality improvement (QI) and comparative effectiveness research (CER); and the Electronic Data Methods (EDM) Forum. These collectively built a national clinical electronic data infrastructure that used prospective, patient-centered outcomes data and connected different clinical databases for CER, which provided a foundation for the PCORI-supported National Patient-Centered Clinical Research Network (PCORnet). The enhanced registries program provided successful models of learning health systems. A major EDM Forum achievement is the launch of a new open-access electronic journal – eGEMs – that has published over 100 papers with over 75,000 downloads in less than three years of existence and is available in PubMed Central. The EDM Forum has created a multi-disciplinary learning community. It supports collaborative methods projects at the intersection of clinical informatics, research, QI and clinical care.

Dr. Randhawa worked with the Developing Evidence to Inform Decisions about Effectiveness (DEcIDE), Centers for Education and Research on Therapeutics (CERTs), and the Evidence-based Practice Centers (EPC) programs. He provided scientific direction to a DEcIDE project to create a new distributed research network in ambulatory care (DARTNet), which evolved into an independent, self-sustaining organization called the DARTNet Institute. DARTNet sustainably implemented screening for depression in primary care. He provided direction to another DEcIDE project to develop a clinical decision support tool for primary care to evaluate patients for BRCA testing, which helps to implement USPSTF recommendations. The tool has been adapted for use by the CDC. He provided program guidance to several EPC projects that evaluated genomic tests for the CDC-sponsored Evaluation of Genomic Applications in Practice and Prevention (EGAPP) working group.

Dr. Randhawa’s last role at AHRQ was in the division of health IT, where he helped in the strategic planning for future investments and served as a project officer for health IT grants. He has authored numerous publications, serves as a peer-reviewer for scientific journals, and served in several national committees, including the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS), steering committee of EGAPP, planning board of a FDA-supported national medical device surveillance system, and steering committee of the PCORnet.

 

SUMMARY:

Topic:  Conducting Large-Scale Treatment Research in Cancer within the OHDSI Network

Speakers: George Hripcsak, M.D., M.S., Columbia University, and Gurvaneet Randhawa, M.D., Ph.D., NCI

Date: Wednesday, February 14, 2018

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Drs. Hripcsak and Gurvaneet's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Drs. Hripcsak and Gurvaneet will present on site at the Shady Grove building.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. Junjun ZhangThe Ontario Institute for Cancer Research (OICR) has been leading several large-scale international collaborations in cancer genomics with a focus on big data management and high-throughput computational analyses. These projects include: the International Cancer Genome Consortium (ICGC) whose goal is to categorize the genomes of 25,000 tumors by 2018; the Pan-Cancer Analysis of Whole Genomes (PCAWG) with the goal to uniformly analyze the whole genomes of over 2,800 ICGC patients; and the Cancer Genome Collaboratory which is a newly built compute cloud to facilitate computational analyses on the ICGC dataset estimated at 5PB by project completion. In this presentation, Junjun will describe how OICR addresses the big data challenges in these projects, and how OICR will leverage the established infrastructure, expertise and partnership to tackle its next challenge: ICGG-ARGO which is an international collaboration to catalog cancer genome alterations and link them to therapeutic outcome in 100,000 patients.

Session details...

 

BIO:

Junjun Zhang leads the bioinformatics and data curation team that is an integral part of the software development group at OICR. He has extensive experience in designing/building automated computational workflow system and integrated biological databases, such as the Database of Genomic Variants (DGV), the International Cancer Genome Consortium (ICGC) data portal, and the NCI Genomic Data Commons (GDC) data portal. Prior to joining OICR in 2008, he worked as a bioinformatics developer in the Centre for Applied Genomics at Toronto's SickKids hospital developing bioinformatics tools/algorithms for biological data management, assembling/annotating human genomes, and identifying genomic variants from large-scale microarray and NGS datasets.

SUMMARY:

Topic:  Addressing Big Data Challenges in the ICGC Project

Speaker: Junjun Zhang, Ontario Institute for Cancer Research (OICR) 

Date: Wednesday, January 31, 2018

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Mr. Zhang's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Mr. Zhang will give his presentation remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. Gina Tourassi and Dr. Paul Fearn

Pathology reports are a primary source of information for cancer registries, which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this talk we will present an update on the NCI-DOE pilot for cancer surveillance, discussing deep learning technology developed and highlighting both theoretical and practical perspectives that are relevant to natural language processing of clinical reports. Using different deep learning architectures, we will present benchmark studies for various information extraction tasks and discuss their importance in supporting a comprehensive and scalable national cancer surveillance program. 

Session details...


BIOS:

Dr. Gina Tourassi is the founding Director of the Health Data Sciences Institute and Group Leader of Biomedical Sciences, Engineering and Computing at the Oak Ridge National Laboratory (ORNL). Concurrently, she holds appointments as an adjunct Professor of Radiology at Duke University and the University of Tennessee and as a joint UT-ORNL Professor of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee at Knoxville. Her research interests include medical imaging, biomedical informatics, clinical decision support systems and data-driven biomedical discovery. Her scholarly work has led to nine U.S. patents and innovation disclosures and more than 230 peer-reviewed journal articles, conference proceedings articles, and book chapters. Her research in medical imaging has been featured in numerous high-profile publications such as the MIT Science and Technology Review, Oncology Times and the Economist. Dr. Tourassi has served as Associate Editor of the scientific journals Radiology and Neurocomputing, and as a Guest Associate Editor of Medical Physics. She is elected Fellow of the American Institute of Medical and Biological Engineering (AIMBE), the American Association of Medical Physicists (AAPM) and the International Society for Optics and Photonics (SPIE). For her leadership in the Joint Design of Advanced Computing Solutions for Cancer initiative, she received the DOE Secretary’s Appreciation Award in 2016. In 2017, she received ORNL Distinguished Researcher award and Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Dr. Tourassi holds a B.S. degree in Physics from Aristotle University of Thessaloniki, Greece, and a Ph.D. in Biomedical Engineering from Duke University.

Dr. Paul Fearn is Chief of the Surveillance Informatics Branch for the National Cancer Institute (NCI) Surveillance Research (SEER) Program, advancing applications of natural language processing, machine learning, and other informatics tools and methods to support cancer registries and cancer surveillance. Previously, he was Director of Biomedical Informatics at Fred Hutchinson Cancer Research Center and instigator of the Hutch Integrated Data Repository and Archive (HIDRA). He has been the Informatics Manager for the Department of Surgery and the Office of Strategic Planning and Innovation at Memorial Sloan-Kettering Cancer Center (MSKCC), where he initiated and led the Caisis project, an open-source system that is currently used at multiple centers. Paul has a B.A. in Spanish from the University of Houston, biostatistics training from the University of Texas School of Public Health in Houston, an M.B.A. from the New York University Stern School of Business, and a Ph.D. in Biomedical and Health Informatics from the University of Washington School of Medicine. He has more than 20 years of experience in cancer research informatics at Baylor College of Medicine, MSKCC, Fred Hutch and with the NCI SEER program.

SUMMARY:

Topic:  Deep Learning Methods for Scalable Information Extraction From Path Reports: An Update from the NCI-DOE Pilot for Cancer Surveillance

Speakers: Gina Tourassi, Ph.D., University of Tennessee, Knoxville, Oak Ridge National Laboratory & Paul Fearn, Ph.D., M.B.A., Division of Cancer Control and Population Sciences, NCI

Date: Wednesday, January 17, 2018

Time: 11 AM – 12 PM ET

You are invited to listen to Drs. Tourassi and Fearn's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Drs. Tourassi and Fearn will give their presentation onsite at Shady Grove.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Medical imaging in oncology has traditionally been restricted to the diagnosis and staging of cancer. But technological advances in Artificial Intelligence (AI) are moving imaging modalities into the heart of patient care. Imaging can address a critical barrier in precision medicine as solid tumors can be spatial and temporal heterogeneous, and the standard approach to tumor sampling, often invasive needle biopsy, is unable to fully capture the spatial state of the tumor. Radiomics refers to the automatic quantification of this radiographic phenotype. Radiomic methods heavily rely on AI technologies, in specific engineered and deep-learning algorithms, to quantify phenotypic characteristics that can be used to develop non-invasive biomarkers. In this talk, Dr. Aerts will discuss recent developments from his group and collaborators performing research at the intersection of radiology, bioinformatics, and data science. Also, he will discuss recent work of building a computational image analysis system to extract a rich radiomics set and use these features to build radiomic signatures. The presentation will conclude with a discussion of future work on building integrative systems incorporating both molecular and phenotypic data to improve cancer therapies.

Objectives:

• Learn about the motivation and methodology of AI technologies in Radiology

• Learn about the existing and future potential role of radiologic AI with other –omics data for precision medicine.

Session details...


BIO:

Dr. Hugo Aerts is an Associate Professor at Harvard Medical School and Director of the Computational Imaging and Bioinformatics Laboratory (CIBL) at the Dana-Farber Cancer Institute. Dr. Aerts’ group focuses on the development and application of advanced computational approaches applied to medical imaging data, pathology, and genomic data. Furthermore, he is a PI-member of the Quantitative Imaging Network (QIN) and NIH's Informatics Technology for Cancer Research (ITCR) initiatives.

SUMMARY:

Topic:  Artificial Intelligence in Radiology

Speaker: Hugo Aerts, Ph.D., Dana Farber Cancer Center and Harvard Medical School

Date: Wednesday, November 8, 2017

Time: 11 AM – 12 PM ET

 

You are invited to listen to Dr. Aerts' presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Aerts will give his presentation remotely via WebEx.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Picture of Venu GovindarajuWe present an overview of two decades of innovation in handwriting recognition at the Govindaraju lab at the University at Buffalo and offer a perspective on the evolution of research in this area and the future of the field.  We highlight our seminal work in handwriting recognition that was at the core of the first handwritten address interpretation system used by the U.S. Postal Service, described as one of the first practical success stories of AI (Daphne Koller, Stanford, at the CCC symposium on Computing Research that changed the World) and as a shining example of AI for the Social Good (Eric Horvitz, Microsoft Research).  We journey through the HWR landscape, from lexicon-based to lexicon-free approaches, and from heuristics-driven techniques to the principled methodologies that we introduced.  We explore a sample of the variety of impactful applications that resulted from our research, from the processing of healthcare forms for the NYS Department of Health for deriving early indicators of outbreaks, to access to historical documents through word spotting, transcript mapping and other indexing schemes for digital libraries, to award-winning pre-processing techniques and multilingual OCR solutions for automated machine translation for armed forces in the theater.  We introduce the novel concept of accents in handwriting and our pioneering use of handwritten CAPTCHAs to enhance security.  We end with a look at some of the challenging problems that we are working on in the digital humanities space and new ideas to explore such as the potential use of whiteboard recognition technologies in the flipped classroom setting.  


Session details...

BIO:

Dr. Venu Govindaraju, University at Buffalo Vice President for Research and Economic Development and SUNY Distinguished Professor of Computer Science and Engineering, is founding director of the Center for Unified Biometrics and Sensors. His research focuses on  machine learning and pattern recognition primarily in Document Image Analysis and Biometrics. His pioneering work in handwriting recognition was at the core of the first handwritten address interpretation system used by the U.S. Postal Service as well as postal services in Australia and the UK. An extraordinary researcher, he has been a Principal or Co-Investigator of sponsored projects funded for nearly 65 million dollars.

He has published widely, coauthoring about 425 refereed papers. He has served on numerous professional and editorial boards, including IEEE Transactions (Pattern Analysis and Machine Intelligence; Information and Forensics Security) and as editor-in-chief of the IEEE Biometrics Councils Compendium. Dr. Govindaraju is a Fellow of the ACM (Association for Computing Machinery), the IEEE (Institute of Electrical and Electronics Engineers), the AAAS (American Association for the Advancement of Science), the IAPR (International Association of Pattern Recognition) and the SPIE (International Society of Optics and Photonics). 

He received the 2001 International Conference on Document Analysis and Recognition Young Investigator award, the 2004 MIT Global Indus Technovator Award, the 2010 IEEE Technical Achievement Award and the Indian Institute of Technology (IIT) Distinguished Alumnus Award (2014). Recently, Dr. Govindaraju received the 2015 IAPR/ICDAR Outstanding Achievements Award and was named a Fellow of the National Academy of Inventors. He also has supervised the dissertations of 36 doctoral students. In Dec. 2016, he received UB’s Excellence in Graduate Student Mentoring Award, recognition of his great efforts in nurturing the next generation of scientists.

SUMMARY:

Topic:  Handwriting Recognition: A Perspective on Two Decades of Innovations

Speaker: Venu Govindaraju, Ph.D., University of Buffalo

Date: Wednesday, October 25, 2017

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Dr. Govindaraju's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Govindaraju will give his presentation remotely via WebEx.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Picture of Anant Madabhushi Traditional biology generally looks at only a few aspects of an organism at a time and attempts to molecularly dissect diseases and study them part by part with the hope that the sum of knowledge of parts would help explain the operation of the whole. Rarely has this been a successful strategy to understand the causes and cures for complex diseases. The motivation for a systems based approach to disease understanding aims to understand how large numbers of interrelated health variables, gene expression profiling, its cellular architecture and microenvironment, as seen in its histological image features, its 3 dimensional tissue architecture and vascularization, as seen in dynamic contrast enhanced (DCE) MRI, and its metabolic features, as seen by Magnetic Resonance Spectroscopy (MRS) or Positron Emission Tomography (PET), result in emergence of definable phenotypes. At the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University, we have been developing computerized knowledge alignment, representation, and fusion tools for integrating and correlating heterogeneous biological data spanning different spatial and temporal scales, modalities, and functionalities. These tools include computerized feature analysis methods for extracting subvisual attributes for characterizing disease appearance and behavior on radiographic (radiomics) and digitized pathology images (pathomics). Unlike radiomics and pathomics which are supervised feature analysis approaches, there has also been a great deal of recent interest in deep learning which enables unsupervised feature generation. In this talk I will discuss the development work in CCIPD on new radiomic and pathomic and deep learning approaches for capturing intra-tumoral heterogeneity and modeling tumor appearance. I will also focus my talk on how these radiomic and pathomic  and deep learning approaches can be applied to predicting disease outcome, recurrence, progression and response to therapy in the context of prostate, brain, rectal, oropharyngeal, and lung cancers. Additionally I will also discuss some recent work on looking at use of pathomics in the context of racial health disparity and creation of more precise and tailored prognostic and response prediction models.

Session details...

BIO:

Dr. Anant Madabhushi is the Director of the Center for Computational Imaging and Personalized Diagnostics (CCIPD) and the F. Alex Nason Professor II in the Departments of Biomedical Engineering, Pathology, Radiology, Radiation Oncology, Urology, General Medical Sciences, and Electrical Engineering and Computer Science at Case Western Reserve University. He is also a member of the Case Comprehensive Cancer Center. 

Dr. Madabhushi received his Bachelors Degree in Biomedical Engineering from Mumbai University, India in 1998 and his Masters in Biomedical Engineering from the University of Texas, Austin in 2000. In 2004 he obtained his Ph.D. in Bioengineering from the University of Pennsylvania. He joined the Department of Biomedical Engineering, Rutgers University as an Assistant Professor in 2005. He was promoted to Associate Professor with Tenure in 2010. In 2012 he accepted the position of Associate Professor at Case Western Reserve University, Department of Biomedical Engineering and is currently directing a center on computational imaging and personalized diagnostics. He was promoted to full professor in 2014.

Dr. Madabhushi has authored over 120 peer-reviewed journal publications  and over 150 conferences papers and delivered over 175 invited talks and lectures both in the US and abroad. He has 25 issued patents in the areas of medical image analysis, computer-aided diagnosis, and computer vision. He is an Associate Editor for IEEE Transactions on Biomedical Engineering, IEEE Transactions on Biomedical Engineering Letters, BMC Cancer, BMC Medical Imaging, Journal of Medical Imaging and Medical Image Analysis (MedIA). He is also on the Editorial Board of the Journal Analytical and Cellular Pathology. He has been the recipient of a number of awards for both research as well as teaching, including the Department of Defense New Investigator Award in Lung Cancer (2014), the Coulter Phase 1 and Phase 2 Early Career award (2006 and 2008), and the Excellence in Teaching Award (2007-2009), along with a number of technology commercialization awards. He is also a Wallace H. Coulter Fellow, a Fellow of the American Institute of Medical and Biological Engineering (AIMBE), and a Senior IEEE member. In 2015 he was named by Crains Cleveland Business Magazine as one of Forty under 40 making positive impact to business in North East Ohio. His research work has received grant funding from the National Cancer Institute (NIH), National Science Foundation, the Department of Defense, private foundations, and from Industry.

He is also the co-founder of Ibris Inc. a startup company focused on developing image based assays for breast cancer prognosis. He is also the conference chair for the new Digital Pathology Conference to be held annually in conjunction with the SPIE Medical Imaging Symposium.

SUMMARY:

Topic:  Radiomics, Pathomics and Deep Learning: Role of Computational Imaging in Precision Medicine

Speaker: Anant Madabhushi, Ph.D., Case Western Reserve University

Date: Wednesday, October 11, 2017

Time: 11 AM – 12 PM ET

You are invited to listen to Dr. Madabhushi's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Madabhushi will give his presentation on site at the NCI Shady Grove Building.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Picture of Mark MusenWhen left to their own devices, scientists do a terrible job creating the metadata that describe the experimental datasets that make their way in online repositories.  The lack of standardization makes it extremely difficult for other investigators to find relevant datasets, to perform secondary analyses, and to integrate those datasets with other data.  At Stanford, we are leading the Center for Expanded Data Annotation and Retrieval (CEDAR), a center of excellence in the NIH Big Data to Knowledge Program, which has the goal of enhancing the authoring of experimental metadata to make online datasets more useful to the scientific community.  CEDAR technology includes methods for managing a library of templates for representing metadata, and interoperability with a repository of biomedical ontologies that normalize the way in which the templates may be filled out.  CEDAR uses a repository of previously authored metadata from which it learns patterns that drive predictive data entry,  making it easier for metadata authors to perform their work.  Ongoing collaborations with several major research projects are allowing us to explore how CEDAR may ease access to scientific data sets stored in public repositories and enhance the reuse of the data to drive new discoveries.

Session details...

 

 

BIO:

Dr. Musen is Professor of Biomedical Informatics and of Biomedical Data Science at Stanford University, where he is Director of the Stanford Center for Biomedical Informatics Research.  Dr. Musen conducts research related to open science, metadata for enhanced annotation of scientific data sets, intelligent systems, reusable ontologies, and biomedical decision support.  His group developed Protégé, the world’s most widely used technology for building and managing terminologies and ontologies. He is principal investigator of the National Center for Biomedical Ontology, one of the original National Centers for Biomedical Computing created by the U.S. National Institutes of Heath (NIH).  He is principal investigator of the Center for Expanded Data Annotation and Retrieval (CEDAR).  CEDAR is a center of excellence supported by the NIH Big Data to Knowledge Initiative, with the goal of developing new technology to ease the authoring and management of biomedical experimental metadata.  Dr. Musen directs the World Health Organization Collaborating Center for Classification, Terminology, and Standards at Stanford University, which has developed much of the information infrastructure for the authoring and management of the 11th edition of the International Classification of Diseases (ICD-11). 

Dr. Musen was the recipient of the Donald A. B. Lindberg Award for Innovation in Informatics from the American Medical Informatics Association in 2006.  He has been elected to the American College of Medical Informatics, the Association of American Physicians, the International Academy of Health Sciences Informatics, and the National Academy of Medicine.  He is founding co-editor-in-chief of the journal Applied Ontology.

SUMMARY:

Topic:  Making online data searchable, accessible, and reusable: The Center for Expanded Data Annotation and Retrieval

Speaker: Mark A. Musen, M.D., Ph.D., Stanford University

Date: Wednesday, September 13, 2017

Time: 11 AM – 12 PM ET

Room: Seminar 408/410

You are invited to listen to Dr. Musen's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Musen will give his presentation in person at NCI.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

Angel Pizarro

The growing number of uses for artificial intelligence (AI), machine learning (ML) and deep learning (DL) continues to drive the development of cutting-edge technology solutions. Biomedical research and medical care are fields that are poised to be dramatic change as they start to integrate computer vision, predictive modeling, natural language understanding, and recommendation engines within standard practice. In this talk, we will review why AI and ML are hard problems to tackle, describe some cutting edge examples in biomedical research and other industries that are applying these techniques to create materially better solutions, and then dive into the details of the family of intelligent services at AWS that provide cloud-native machine learning and deep learning technologies to address a wide range of research needs. We will focus specifically on deep learning applications and products, such as the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale. Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud.

Session details...




BIO:

Angel Pizarro leads the global genomics,  life science, and precision medicine initiatives within the Research and Technical Computing at Amazon Web Services. He has over 17 years of experience in bioinformatics, supporting a broad range of technologies such as high-throughput sequencing, proteomics, and metabolomics. Prior to joining AWS in 2013, he lead a bioinformatics research team at the University of Pennsylvania School of Medicine, developing systems and algorithms to support a broad set of research problems focused on genomic expression and cardiovascular research.

SUMMARY:

Topic:  Machine Learning on the Cloud with MXNet

Speaker: Angel Pizarro, Scientific Computing at Amazon Web Services

Date: Wednesday, July 19, 2017

Time: 11 AM – 12 PM ET

Room: Seminar Room 110 (Terrace East)

You are invited to listen to Mr. Pizarro's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Mr. Pizarro will give his presentation in person at NCI.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.



Modern information systems, storage devices and recording formats have led to unprecedented growths in scientific and social data. These advancements have resulted in the Big Data (BD) paradigm – enormous data collection for processing and analyses that can provide new information not otherwise gleaned from smaller disparate data collections.

This presentation will discuss the Open Archival Information System (OAIS) reference model, to address challenges posed by BD. Examples from Earth Observing Systems and Biomedical research systems will be shown to elucidate the OAIS. An integrated reference architecture for BD life cycle management will be presented.

Intelligent biomedical archives (IBA) concept and characteristics that differentiate IBA from traditional archives will be highlighted. A functional view of the IBA will be presented for increasing transformation of data to knowledge. Scenario-based examples from biomedical research will be provided to stimulate discussion on approaches to operationalize IBA. A vision for developing true knowledge building systems for biomedical research will be shared.

Session details...

 

BIO:

Since 2016, Dr. Navale is on detail to the Office of Associate Director for Data Science at NIH. His current activities include development of information technology strategies and initiatives for biomedical research. In 2014, he joined NIH, and led the Center for Information Technology Hosting and Storage Service Operations.

From 2000-2014, he served as the Chief of the U.S National Archives and Records Administration (NARA) Digital Preservation and Access program, and was instrumental in modernizing NARA’s Electronic Records Archives Systems. He received the US National Archives Archivist Award for outstanding team contributions made towards agency goals.

He also served as the Department of Commerce, Science and Technology Fellow, and led National Institute of Standards and Technology and Information Storage Industry consortium Metrology working group.

During 1990-2000, he was the Principal Scientist and team member of NASA’s Cassini Huygens probe Mission. In 1998, he received NASA and the European Space Agency Outstanding Team Achievement award. Dr. Navale served as the Chair for International Scientific Data conference sessions.

He received his Doctorate in Chemistry from the George Washington University, Washington, DC.

SUMMARY:

Topic:  Intelligent Biomedical Archives – A Conceptual Architecture for Big Data Science

Speaker: Vivek Navale, Ph.D.

Date: Wednesday, June 7, 2017

Time: 11 AM – 12 PM ET

You are invited to listen to Dr. Navale's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

This session will address the role of computer-aided diagnosis and machine learning in the practice of radiology. The debate format will address the question of whether computers will replace radiologists in 20 years. The session will include information on state-of-the-art machine learning methods, computer-aided diagnosis results, and prognostications on these tools. Impediments to computers replacing radiologists will also be described.

Session details...

 

 

 

BIOS:

Dr. Eliot Siegel is Professor and Vice Chair of Research Information Systems at the University of Maryland School of Medicine, Department of Diagnostic Radiology, as well as Chief of Radiology and Nuclear Medicine for the Veterans Affairs Maryland Healthcare System, both in Baltimore, Maryland.  He has adjunct appointments as Professor of Bioengineering at the University of Maryland College Park and as Professor of Computer Science at the University of Maryland Baltimore County campus.  Dr. Siegel has also served as imaging informatics consultant to the National Cancer Institute.

Under his guidance, the VA Maryland Healthcare System became the first filmless healthcare enterprise in the United States. He has written over 300 articles and book chapters about PACS (Picture Archiving and Communication Systems) and digital imaging, and has edited numerous books on the topic, including Filmless Radiology and Security Issues in the Digital Medical Enterprise. He has made more than 1,000 presentations throughout the world on a broad range of topics involving the use of computers in medicine.

Dr. Siegel has won numerous teaching awards at the University of Maryland including medical school mentor of the year.  He has been named as overall Radiology Researcher of the Year by his peers and separately as Educator of the year.  Dr. Siegel has also been selected by the editorial board of Medical Imaging as one of the top radiologists in the US on multiple occasions. 

Eliot served as “lead” for imaging for the NCI’s caBIG project for several years.  He was overall symposium chairman for the Society of Photo-optical and Industrial Engineers (SPIE) Medical Imaging Meeting for three years, served as chair of Publications for the Society of Computer Applications in Radiology (SIIM) and has been honored as a fellow in that organization and has served multiple terms on the board of directors for SIIM. He served as chairman of the RSNA's Medical Imaging Resource Committee. Dr. Siegel also worked with the IBM “Jeopardy” team to help “educate” the “Dr. Watson” software in the field of medicine.  His areas of interest and responsibility at both the local and national levels include digital imaging and PACS, telemedicine, the electronic medical record, and informatics and artificial intelligence in medicine.

Dr. Brad Erickson received his MD and PhD degrees from Mayo Medical & Graduate School and then did his residency in diagnostic radiology and Neuroradiology fellowship at Mayo Clinic. He went on staff at Mayo Clinic, and was heavily involved in administrative responsibilities implementing a filmless department and then a paperless practice and EMR, including being the Vice Chair for IT at Mayo. More recently, he has refocused on imaging informatics research, receiving NIH grants for brain cancer, multiple sclerosis, and polycystic kidney disease. He is a recognized world expert on the application of deep learning to medical images. He was the founding Chair of the Division of Imaging Informatics, and is currently the Associate Chair for Research in Radiology.

SUMMARY:

Topic:  Will a Computer Replace Radiologists and What Should We Do About It?

Speakers: Eliot Siegel, M.D., and Brad Erickson, M.D., Ph.D.

Date: Wednesday, May 24, 2017

Time: 11 AM – 12 PM ET

You are invited to listen to Drs. Siegel and Erickson's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

SYNOPSIS:

Pediatric cancers are the leading cause of disease-related death in children, but are defined as a rare disease when contrasted to adult tumors. Because of this classification, pediatric cancer discovery efforts are challenging due to a more limited basic and translational data-driven research infrastructure. As such, harnessing the potential for accelerated discovery through large-scale molecular/genomic data-generation and analysis platforms requires new approaches and tools for collaborative discovery on behalf of the rare disease patient-community.  The Children’s Hospital of Philadelphia and its partnered consortia-based institutions have piloted a series of data-focused initiatives which span biospecimen-driven pediatric cancer research, clinical trials, data storage, analysis, and visualization platform-development.  Covered in the presentation will be our experiences over the past five years in these efforts and the partnered development of CAVATICA, a data analysis platform designed to both facilitate the rapid integration and analysis of genomic data from multiple diseases affecting children and enable transdisciplinary discovery via interoperability with the Genomic Data Commons and other NIH data repositories.

Session details...

 

 

BIO:

Adam Resnick, Ph.D., is the Director of Data Driven Discovery in Biomedicine (D3b) at Children’s Hospital of Philadelphia (CHOP). His research is focused on defining the cell signaling mechanisms of oncogenesis and tumor progression in brain tumors. Resnick’s research lab studies cell signaling cascades and their alterations in pediatric brain tumors to elucidate the molecular and genetic underpinnings of each tumor in an effort to identify and develop targeted therapies. Dr. Resnick serves as Scientific Chair for several consortia-based efforts, including the Children’s Brain Tumor Tissue Consortium (CBTTC) and Pacific Pediatric Neuro-Oncology Consortium (PNOC), which include more than 20 pediatric hospitals across the globe. As director of D3b, Dr. Resnick leads a multidisciplinary team to build and support a scalable, patient-focused healthcare and educational discovery ecosystem on behalf of all children.

SUMMARY:

Topic:  Innovation Through Collaboration: New Models Emerging in Pediatrics for an Integrated Data-driven Healthcare Ecosystem

Speaker: Adam Resnick, Ph.D.

Date: Wednesday, May 10, 2017

Time: 11 AM – 12 PM ET

WebEx:  https://cbiit.webex.com/cbiit/onstage/g.php?MTID=eb4d9b5142006405791fda136785bf8ee

Event Number: 733 632 295

Event Password: $Peakerseries17

Room: Seminar Room 110, Terrace East Level

You are invited to listen to Dr. Resnick's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

SYNOPSIS:

BD2K Aztec is a global biomedical resource discovery index that allows users to simultaneously search a diverse array of tools. The resources indexed include web services, standalone software, publications, and large libraries composed of many interrelated functions. Aztec will ensure that software tools remain findable in the long term by issuing persistent DOIs and routinely updating metadata for the entire index. Aztec’s established ontologies and robust API support the programmatic query of its entire database, as well as the construction of indexes for specialized subdomains. Aztec is currently in its alpha-release phase (version 1.1), in which it is being evaluated and tested by internal users at UCLA, as well as invited external users at Sage Bionetworks, TSRI, and EMBL-EBI. Their feedback and comments have been documented and incorporated into Aztec's next release.

Join the conversation on Twitter, follow along with @NCI_NCIP and #CBIITSS during the presentation.


Session details...

 

BIO:

Wei Wang is the Leonard Kleinrock Chair Professor in Computer Science at University of California, Los Angeles and the director of the Scalable Analytics Institute (ScAi). She received her Ph.D. in Computer Science from the University of California, Los Angeles in 1999. She was a professor in Computer Science at the University of North Carolina (UNC) at Chapel Hill from 2002 to 2012, and was a research staff member at the IBM Thomas J. Watson Research Center between 1999 and 2002. Dr. Wang's research interests include big data analytics, data mining, bioinformatics and computational biology, and databases. She has filed seven patents, and has published one monograph and more than one hundred seventy research papers in international journals and major peer-reviewed conference proceedings.

Dr. Wang received the IBM Invention Achievement Awards in 2000 and 2001. She was the recipient of an NSF Faculty Early Career Development (CAREER) Award in 2005. She was named a Microsoft Research New Faculty Fellow in 2005. She was honored with the 2007 Phillip and Ruth Hettleman Prize for Artistic and Scholarly Achievement at UNC. She was recognized with an IEEE ICDM Outstanding Service Award in 2012, an Okawa Foundation Research Award in 2013, and an ACM SIGKDD Service Award in 2016. Dr. Wang has been an associate editor of the IEEE Transactions on Knowledge and Data EngineeringIEEE Transactions on Big DataACM Transactions on Knowledge Discovery in DataJournal of Knowledge and Information SystemsData Mining and Knowledge Discovery, and International Journal of Knowledge Discovery in Bioinformatics. She serves on the organization and program committees of international conferences including ACM SIGMOD, ACM SIGKDD, ACM BCB, VLDB, ICDE, EDBT, ACM CIKM, IEEE ICDM, SIAM DM, SSDBM, RECOMB, BIBM. She was elected to the Board of Directors of the ACM Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics (SIGBio) in 2015.

SUMMARY:

Topic:  Aztec: A Platform to Render Biomedical Software Findable, Accessible, Interoperable, and Reusable

Speaker: Wei Wang

Date: Wednesday, April 26, 2017

Time: 11 AM – 12 PM ET

You are invited to listen to Dr. Wang's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

Michael Crusoe SYNOPSIS:

This talk will introduce the Common Workflow Language (CWL) project. In July 2016 the CWL team released standards that enable the portable, interoperable, and executable description of command line data analysis tools and workflow made from those tools. These descriptions are enhanced by CWL's first class (but optional) support for Docker containers. The state of CWL adoption and examples of bioinformatic collaborations across many continents using CWL will be reviewed. Attendees who want to play with CWL prior to attending the presentation are invited to go through the "Gentle Introduction to the Common Workflow Language" tutorial on any OS X or Linux machine on their own time: http://www.commonwl.org/v1.0/UserGuide.html 

Session details...

 

BIO:

Michael R. Crusoe is one of the co-founders of the CWL project and is the CWL Community Engineer. His facilitation, technical contributions, and training on behalf of the project draw from his time as the former lead developer of C. Titus Brown's k-h-mer project, his previous career as a sysadmin and programmer, and his experiences in various Free and Open Source Software communities. This is not Michael's first time working on a standards project as he was the technical author of the International Labour Organization's Seafarers' Identity Card (2003) standard which is in force and ratified by 32 countries. Based out of Europe for the last year and a half, Michael has enjoyed partnering with ELIXIR and other European research networks to build collaborations across that continent and across the world. When not traveling to promote and improve CWL, Michael lives with his husband in their new home city: Vilnius, Lithuania.

SUMMARY:

Topic:  Portable Bioinformatic Workflows with the Common Workflow Language

Speaker: Michael Crusoe

Date: Wednesday, March 29, 2017

Time: 11 AM – 12 PM ET

You are invited to listen to Mr. Crusoe's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Tina Hernandez-Boussard SYNOPSIS:

Prostate cancer is the most common malignancy in men and newly diagnosed men face complex treatment choices, each with different risks of acquired morbidities, including patient-centered outcomes (PCOs). Current government initiatives highlight the need to incorporate PCOs into healthcare quality metric evaluations and the widespread implementation of electronic health records (EHRs) provides opportunities to do so. However, efforts to assess quality metrics in EHRs have been limited because most relevant data are not reliably captured in structured formats. Instead they are buried as non-structured, free text recorded by clinicians. Leveraging the power of computational resources for processing the vast amount of medical information residing in EHRs, we achieve automation and precision in the evaluation of both process and outcome quality metrics, including metrics focused on PCOs.

To develop our approach, we first built a patient cohort using ICD-9/10 diagnosis codes to identify prostate cancer patients. Patients are confirmed in the California Cancer Registry, which returns tumor characteristics and treatment data on all patients with a confirmed cancer diagnosis, including complete historical record of disease pathology. Next we create novel ontological representations of quality metrics, many that are non-prostate specific. Each quality metric determines the target terms and concepts to extract from the EHRs. These terms may include diagnostic procedures and tests and their results, therapeutic procedures, and drugs. Terms are mapped to a standardized medical vocabulary (e.g., SNOMED or RxNorm), enabling us to represent the elements of a metric by a concept domain and its permissible values. The structured representation of the quality metric terms are used to create quality phenotypes, which are rules involving the temporal order of components of the quality metrics. Finally, we use data mining algorithms, including Natural Language Processing (NLP) technologies to parse the clinical narrative text and extract pertinent structured information. While we test our methodology in prostate cancer patients, these approaches are applicable to all cancer patients and are the basis of a learning healthcare system. This presentation will demonstrate the feasibility of using our methods to increase the usability of existing EHRs and enhance the efficiency and accuracy of quality measurement in cancer patients, including PCO measurements.

Session details...


BIO:

Dr. Tina Hernandez-Boussard is an Associate Professor of Medicine (Biomedical Informatics) and Biomedical Data Sciences at Stanford University. Her background and expertise is in the field of computational biology, with concentration on accountability measures and health policy. A key focus of her research is the application of novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery.

SUMMARY:

Topic:  Generating Value from EHRs for Quality Measure Analytics in Prostate Cancer Patients

Speaker: Tina Hernandez-Boussard, Ph.D.

Date: Wednesday, February 1, 2017

Time: 11 AM – 12 PM ET

Room: 2E908

You are invited to listen to Dr. Hernandez-Boussard's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. 

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.