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AIC Seminar Series

Cancer: A Computational Disease That AI Can Cure

Jeff ShragerSRI[Home Page]

Notice:  Hosted by Vinay Chaudhri

Date:  2013-01-16 at 16:00

Location:  EJ228 (SRI E building)  (Directions)

   Abstract

Cancer kills millions of people each year. From an AI perspective, finding effective treatments for cancer is a high-dimensional search problem characterized by many molecularly distinct cancer subtypes, many potential targets and drug combinations, and a dearth of high quality data to connect molecular subtypes and treatments to responses. The broadening availability of molecular diagnostics, electronic medical records, and biomedical knowledge bases presents both opportunities and challenges to apply AI techniques to personalize and improve cancer treatment. Research opportunities include adaptively planning and executing individual treatment experiments across the whole patient population, inferring the causal mechanisms of tumors, predicting drug response in individuals, and generalizing these findings to new cases. In this talk I will discuss some of these opportunities and challenges, and describe a few specific technical approaches whose goal is to treat each patient in accord with the best available knowledge, and to continually update that knowledge to benefit subsequent patients. Achieving this goal is a worthy grand challenge for AI.

   Bio for Jeff Shrager

Jeff Shrager is a member of the AURA project. Before joining SRI he was the co-founder and CTO of CollabRx, Inc. Ever since his PhD work at CMU (in 1985), Jeff has been pursuing the understanding and molding of scientific reasoning and discovery.

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