M.D., Ph.D., Co-Founder, Chief Medical Officer, Omics Data Automation
Biography
Dr. Christopher Corless is a Co-Founder of Omics Data Automation and also serves as the Executive Director of Knight Diagnostic Laboratories at Oregon Health & Sciences University. Dr. Corless has expertise in applying molecular diagnostics to the classification and prognostication of solid tumors. Dr. Corless received his M.D. and Ph.D. from Washington University in St. Louis. He did his residency training in anatomic pathology at Brigham & Women's Hospital in Boston, Mass., where he also completed fellowships in gastrointestinal and genitourinary pathology. He is an author or coauthor on more than 280 publications.
AI and Data Sciences Showcase:
Omics Data Automation
ODA makes tools that aggregate data from EHR, omics and imaging to provide analytics that improve patient outcomes, reduce cost and expand access.
Multi-Modal Learning For AI and IA: Applications To Cancer
The amount and diversity of data generated in the care and treatment of cancer patients is ever increasing, and we will describe how Omics Data Automation Framework store, process, and manage data from large, heterogeneous and siloed data sets such as Omics, Imaging and EHR / Clinical Trials data bases. The talk will cover future directions on how intelligent assistant/causal learning from multimodal data for cancer patients from federated systems will improve patient outcomes in Prostate Cancer and accelerate progress in basic science and clinical trials.
Session Abstract – PMWC 2020 Silicon Valley
Track 7 - January 22 9.00 A.M.-3.45 P.M.,Track 6 - January 23 11.15 A.M.-11.30 A.M.,Track 2 - January 24 11.15 A.M.-4.00 P.M.
The PMWC 2020 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.
