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

Text-messaging (SMS, WeChat etc)-Based Interventions (624) Machine Learning (1400) Evaluation and Research Methodology for mHealth (195) Mobile Health (mhealth) (2776) Chronic Conditions (219) Prevention and Health Promotion (899) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27779, first published .
Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis

Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis

Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis

Authors of this article:

Harry Klimis1, 2 Author Orcid Image ;   Joel Nothman3 Author Orcid Image ;   Di Lu3 Author Orcid Image ;   Chao Sun3 Author Orcid Image ;   N Wah Cheung1, 4, 5 Author Orcid Image ;   Julie Redfern1 Author Orcid Image ;   Aravinda Thiagalingam1, 2 Author Orcid Image ;   Clara K Chow1, 2 Author Orcid Image
Article Authors Cited by (6) Tweetations (9) Metrics

Journals

  1. Kim E, Brown L, Seltzer E, Hartzell‐Leggin D, Borodyanskaya Y, Andy U, Rosin R, Whitmore K, Newman D, Arya L. Development of a patient‐centered text message‐based platform for the self‐management of interstitial cystitis/bladder pain syndrome symptoms. Neurourology and Urodynamics 2023;42(2):510 View
  2. Chow C, Klimis H, Thiagalingam A, Redfern J, Hillis G, Brieger D, Atherton J, Bhindi R, Chew D, Collins N, Andrew Fitzpatrick M, Juergens C, Kangaharan N, Maiorana A, McGrady M, Poulter R, Shetty P, Waites J, Hamilton Craig C, Thompson P, Stepien S, Von Huben A, Rodgers A. Text Messages to Improve Medication Adherence and Secondary Prevention After Acute Coronary Syndrome: The TEXTMEDS Randomized Clinical Trial. Circulation 2022;145(19):1443 View
  3. Jaltotage B, Ihdayhid A, Lan N, Pathan F, Patel S, Arnott C, Figtree G, Kritharides L, Shamsul Islam S, Chow C, Rankin J, Nicholls S, Dwivedi G. Artificial Intelligence in Cardiology: An Australian Perspective. Heart, Lung and Circulation 2023;32(8):894 View
  4. Nelson L, Spieker A, LeStourgeon L, Greevy Jr R, Molli S, Roddy M, Mayberry L. The Goldilocks Dilemma on Balancing User Response and Reflection in mHealth Interventions: Observational Study. JMIR mHealth and uHealth 2024;12:e47632 View
  5. Nelson A, Pagidipati N, Bosworth H. Improving medication adherence in cardiovascular disease. Nature Reviews Cardiology 2024;21(6):417 View
  6. Lewin S, Chetty R, Ihdayhid A, Dwivedi G. Ethical challenges and opportunities in applying artificial intelligence to cardiovascular medicine. Canadian Journal of Cardiology 2024 View