Published on in Vol 11 (2024)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/49577, first published
.
Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis
Health Care Professionals’ Views on the Use of Passive Sensing, AI, and Machine Learning in Mental Health Care: Systematic Review With Meta-Synthesis
Journals
- Bidargaddi N, Leibbrandt R, Paget T, Verjans J, Looi J, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. DIGITAL HEALTH 2024;10 View
- Hoose S, Králiková K. Artificial Intelligence in Mental Health Care: Management Implications, Ethical Challenges, and Policy Considerations. Administrative Sciences 2024;14(9):227 View
- Cormier M, Orr M, Kaser A, MacDonald H, Chorney J, Meier S. Sleep well, worry less: A co-design study for the development of the SMILE app. DIGITAL HEALTH 2024;10 View
- Wu W, Zuo E, Zhang W, Meng X. Multi-physiological signal fusion for objective emotion recognition in educational human–computer interaction. Frontiers in Public Health 2024;12 View
- Levkovich I, Rabin E, Brann M, Elyoseph Z. Large language models outperform general practitioners in identifying complex cases of childhood anxiety. DIGITAL HEALTH 2024;10 View