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

Machine Learning (47) Mobile Health (mhealth) (2752) Text-messaging (SMS, WeChat etc)-Based Interventions (621) Engagement with and Adherence to Digital Health Interventions, Law of Attrition (458) Diabetes-specific EHR Improvements (29) Machine Learning (1374) Diabetes (150) Artificial Intelligence in Diabetes Care and Prevention (22) Diabetes Prevention (77)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47122, first published .
Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study

Authors of this article:

Danissa V Rodriguez1 Author Orcid Image ;   Ji Chen1 Author Orcid Image ;   Ratnalekha V N Viswanadham1 Author Orcid Image ;   Katharine Lawrence1, 2 Author Orcid Image ;   Devin Mann1, 2 Author Orcid Image
Article Authors Cited by Tweetations (7) Metrics

Danissa V Rodriguez   1 , PhD ;   Ji Chen   1 , PhD ;   Ratnalekha V N Viswanadham   1 , PhD ;   Katharine Lawrence   1, 2 , MPH, MD ;   Devin Mann   1, 2 , MS, MD

1 New York University Grosman School of Medicine, New York, NY, United States

2 New York University Langone Health, New York, NY, United States

Corresponding Author: