This paper is in the following e-collection/theme issue:

Mobile Health (mhealth) (3562) Digital Biomarkers and Digital Phenotyping (302) Ecological Momentary Assessment (EMA) (424) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1776) Chronic Conditions (464) Depression and Mood Disorders; Suicide Prevention (1731)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70871, first published .
Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation

Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation

Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation

Authors of this article:

Zongqi Xia1 Author Orcid Image ;   Prerna Chikersal2 Author Orcid Image ;   Shruthi Venkatesh1 Author Orcid Image ;   Elizabeth Walker1 Author Orcid Image ;   Anind K Dey3 Author Orcid Image ;   Mayank Goel2 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Vevera A, Ianculescu M, Alexandru A. A Digital Health Platform for Remote and Multimodal Monitoring in Neurodegenerative Diseases. Future Internet 2025;17(12):571 View
  2. Baller E, Cooper E, Schindler M, Bar-Or A, Fox M, Shinohara R, Satterthwaite T. Depression as a Disease of White Matter Network Disruption: Learning From Multiple Sclerosis. Biological Psychiatry 2025 View