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

Ecological Momentary Assessment (EMA) (297) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) mHealth for Data Collection and Research (917) Diabetes Self-Management (464) Glucose Tracking and Self-Monitoring of Blood Glucose (152) Machine Learning (1400)

Published on in Vol 10, No 3 (2022): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/21959, first published .
Using Momentary Assessment and Machine Learning to Identify Barriers to Self-management in Type 1 Diabetes: Observational Study

Using Momentary Assessment and Machine Learning to Identify Barriers to Self-management in Type 1 Diabetes: Observational Study

Using Momentary Assessment and Machine Learning to Identify Barriers to Self-management in Type 1 Diabetes: Observational Study

Authors of this article:

Peng Zhang1, 2 Author Orcid Image ;   Christopher Fonnesbeck3 Author Orcid Image ;   Douglas C Schmidt1, 2 Author Orcid Image ;   Jules White1 Author Orcid Image ;   Samantha Kleinberg4 Author Orcid Image ;   Shelagh A Mulvaney5, 6, 7 Author Orcid Image
Article Authors Cited by (4) Tweetations (8) Metrics

Peng Zhang   1, 2 , PhD ;   Christopher Fonnesbeck   3 , PhD ;   Douglas C Schmidt   1, 2 , PhD ;   Jules White   1 , PhD ;   Samantha Kleinberg   4 , PhD ;   Shelagh A Mulvaney   5, 6, 7 , PhD

1 Department of Computer Science, School of Engineering, Vanderbilt University, Nashville, TN, United States

2 Data Science Institute, Vanderbilt University, Nashville, TN, United States

3 Department of Biostatistics, Vanderbilt University, Nashville, TN, United States

4 Department of Computer Science, Stevens Institute of Technology, Hoboken, NJ, United States

5 Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States

6 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States

7 School of Nursing, Vanderbilt University, Nashville, TN, United States

Corresponding Author:

  • Peng Zhang, PhD
  • Department of Computer Science
  • School of Engineering
  • Vanderbilt University
  • 1400 18th Ave S
  • Rm 2023
  • Nashville, TN, 37212
  • United States
  • Phone: 1 615-343-8630
  • Email: peng.zhang@vanderbilt.edu