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Upcoming Speakers: Feb 28, 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:

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

June 6, 2018: Dr. Allen Dearry, NCI

May 9, 2018: Andrey Fedorov, Ph.D., Brigham and Women's Hospital and Harvard Medical School

 

 

 

CBIIT Speakers

Oncology 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...

The 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 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...

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...

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