Conference Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 461 - Perils and Opportunities for Analyzing Biological, Behavioral, and Digital Phenotypes of Mental Functions
Type: Invited
Date/Time: Wednesday, August 10, 2022 : 2:00 PM to 3:50 PM
Sponsor: Mental Health Statistics Section
Abstract #320614
Title: Digital Phenotyping for Predicting Depression with Weakly Labeled Data
Author(s): Samprit Banerjee* and Huaian Yu and Hongzhe Zhang
Companies: Weill Medical College, Cornell University and Weill Medical College, Cornell University and University of Pennsylvania

Smartphones provide an interactive interface that can passively measure various aspects of the user’s behavior from device sensors, as well as actively collect self-ratings (e.g. mood, stress etc.) obtained via daily ecological momentary assessment. Taken together with traditional clinical assessments, these measures have the potential to provide unique insight into the outcome trajectory of patients with major depressive disorder undergoing treatment. The potential to predict patient adherence to treatment in clinical trials of psychotherapy is a necessary step to modify future sessions in order to improve compliance and therefore efficacy. There are unique challenges of such predictions due to the noisy nature (missing or under-reporting) of passive and actively mHealth data. The nature of missing passive data is unique in the sense that the missed labels are not observed. In this talk, I will introduce these and other challenges of mHealth data analysis and propose solutions to address such challenges. Finally, I will demonstrate an application of our methods with mHealth data collected on older adults undergoing treatment for major depressive disorder.

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

Back to the full JSM 2022 program