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

Artificial Intelligence (2127) Ethical, Legal, and Social Issues in AI (101) Electronic Health Records (1319) Machine Learning (2074) Depression and Mood Disorders; Suicide Prevention (1689) Intentional Self-Harm (136) Mental Health Issues in Adolescence (636) Pediatrics (159) Human Factors and Usability Case Studies (1005)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57602, first published .
Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study

Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study

Exploring the Perspectives of Pediatric Health Care Providers, Youth Patients, and Caregivers on Machine Learning Suicide Risk Classification: Mixed Methods Study

Authors of this article:

Rohan R Dayal1 Author Orcid Image ;   Pua Lani Yang1 Author Orcid Image ;   Laura Nicole Sisson2 Author Orcid Image ;   Mira Bajaj3 Author Orcid Image ;   Shannon Archuleta1 Author Orcid Image ;   Sophie Yao4 Author Orcid Image ;   Daniel H Park4 Author Orcid Image ;   Hanae Fujii-Rios5 Author Orcid Image ;   Emily E Haroz6 Author Orcid Image
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