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

Digital Health Reviews (1724) Artificial Intelligence (2129) Chronic Conditions (434) Applications of AI (287) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59632, first published .
AI Applications for Chronic Condition Self-Management: Scoping Review

AI Applications for Chronic Condition Self-Management: Scoping Review

AI Applications for Chronic Condition Self-Management: Scoping Review

Authors of this article:

Misun Hwang1 Author Orcid Image ;   Yaguang Zheng2 Author Orcid Image ;   Youmin Cho3 Author Orcid Image ;   Yun Jiang1 Author Orcid Image
Article Authors Cited by (6) Tweetations Metrics

Journals

  1. Cricco R, Segreti A, Ferro A, Beato S, Castaldo G, Ciancio M, Sacco F, Pennazza G, Ussia G, Grigioni F. Advancements in Sensor Technology for Monitoring and Management of Chronic Coronary Syndrome. Sensors 2025;25(15):4585 View
  2. Jeon S, Lee S, Kim E, Eun J, Lee K, Lim H, Lee J. Generative AI Chatbot for Diabetes Management: Formative 2-Part Qualitative Study Using DTalksBot Involving Patients and Clinicians. JMIR Formative Research 2025;9:e72553 View
  3. Du Y, Yang P, Liu Y, Deng C, Li X. Artificial intelligence in chronic disease self-management: current applications and future directions. Frontiers in Public Health 2025;13 View
  4. Nowak K, Nowak A, Jabłońska A, Potaczek A, Salacha J, Dardzińska N, Janczura J. Implementation of noninvasive liver disease screening tools in primary care. Korean Journal of Family Medicine 2025;46(6):381 View
  5. Deng T, Wang C, Wang W, Zhan J. Behavioral three-way decision based multi-attribute decision-making for credible hesitant fuzzy information systems. Engineering Applications of Artificial Intelligence 2026;164:113339 View

Conference Proceedings

  1. Poduri S, Kovvuri L, Uppalapati V, Addepalli L, D V, Lloret J. 2025 International Conference on Biomedical Engineering and Sustainable Healthcare (ICBMESH). Emotion-Augmented Neuro-Symbolic and Quantum-Inspired Adaptive Pain Therapy Using Federated Biofeedback AR/VR Systems View