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Upcoming Speakers: Jan. 31, 2018

An invitation: If you are interested in presenting your work to our diverse audience of informaticists; basic, translational, and clinical researchers; software developers; and others interested in exploring the uses of informatics in cancer research, contact Eve Shalley at eve.shalley@nih.gov or 240-276-5194.

Welcome to the CBIIT Speaker Series Wiki 

The NCI Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics community. 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.

Speakers represent many different institutions, and the topics they address are wide-ranging. View a list of all past speakers, and view their presentations on our NCI CBIIT Speaker Series YouTube playlist!

For help accessing NCI CBIIT Speaker Series files, go to Help Downloading Files.

Location: 9609 Medical Center Drive, Rockville, Maryland 20850

Speaker Series Guidelines for Speakers: Download Word document

Questions or suggestions? If you have questions or would like to recommend a speaker, please email Eve Shalley at eve.shalley@nih.gov

Please refer to the Speaker Calendar below for upcoming speakers.

Upcoming Speakers:

January 31, 2018: Dr. Junjun Zhang, Ontario Institute for Cancer Research (OICR)

February 14, 2018: Dr. Gurvaneet Randhawa, NCI, and Dr. George Hripcsak, Columbia University

February 28, 2018: Dr. George Komatsoulis, American Society of Clinical Oncology (ASCO)

TBD: Allen Dearry, NCI

 

 

CBIIT Speakers

The 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...

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...

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...

We 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...

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