JSM 2015 Online Program

Online Program Home
My Program

Abstract Details

Activity Number: 393
Type: Invited
Date/Time: Tuesday, August 11, 2015 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract #314181
Title: Medallion Lecture: Recent Developments in Machine Learning for Personalized Medicine
Author(s): Michael Kosorok*
Companies: The University of North Carolina at Chapel Hill
Keywords: Machine learning ; Reinforcement learning ; Dynamic treatment regimes ; SMARTs ; Random forests ; Outcome weighted learning

In the past decade there has been an explosion of interest and activity in personalized medicine. The overall goal is to target treatment specifically to each individual so that clinical outcomes for that individual are optimized. One direction of attack is to use patient data to discover decision rules which specify the treatment to use as a function of a vector of features from the patient. Regression and classification are important statistical tools for estimating such rules based on either observational data or data from a randomized trial, and machine learning can help with this because of its ability to artfully handle high dimensional feature spaces with potentially complex interactions. For the multiple decision setting, reinforcement learning, a type of machine learning that is neither regression nor classification, is necessary to properly account for delayed effects. There are several other intriguing nonstandard machine learning tools which can greatly facilitate discovery of decision rules. In this talk, we will discuss the benefits of machine learning in personalized medicine as well as new developments in machine learning inspired by the personalized medicine quest.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program

For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home