|
Activity Number:
|
46
- Recent Developments in Novel Clinical Trial Design and Analysis for Precision Medicine
|
|
Type:
|
Invited
|
|
Date/Time:
|
Sunday, July 28, 2019 : 4:00 PM to 5:50 PM
|
|
Sponsor:
|
ENAR
|
|
Abstract #300379
|
Presentation
|
|
Title:
|
Online Experimentation and Learning Algorithms in a Clinical Trial
|
|
Author(s):
|
Susan Murphy*
|
|
Companies:
|
Harvard University
|
|
Keywords:
|
experimentation;
machine learning;
mobile health;
clinical trial
|
|
Abstract:
|
In this talk we describe two reinforcement learning algorithms we have implemented in a mobile health physical activity trial. These algorithms are designed to tackle two challenges faced by mobile health. The first challenge is that while most treatments delivered by a mobile device have immediate nonnegative (hopefully positive) effects, longer term effects tend to be negative due to user burden. To address this first challenge we add a low variance proxy for the delay effects to the reward (e.g. immediate response) in the learning algorithm. The second challenge is that data on any one individual is very noisy making it difficult for the algorithm to learn. To address this challenge we pool data across participants.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2019 program
|
