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

Methods and New Tools in Mental Health Research (570) Artificial Intelligence (2216) Natural Language Processing (933) Machine Learning (2145) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2190) Infodemiology and Infoveillance (1574) Data Science (369)

Published on in Vol 13 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76051, first published .
Triaging Casual From Critical—Leveraging Machine Learning to Detect Self-Harm and Suicide Risks for Youth on Social Media: Algorithm Development and Validation Study

Triaging Casual From Critical—Leveraging Machine Learning to Detect Self-Harm and Suicide Risks for Youth on Social Media: Algorithm Development and Validation Study

Triaging Casual From Critical—Leveraging Machine Learning to Detect Self-Harm and Suicide Risks for Youth on Social Media: Algorithm Development and Validation Study

Authors of this article:

Sarvech Qadir1 Author Orcid Image ;   Ashwaq Alsoubai2 Author Orcid Image ;   Jinkyung Katie Park3 Author Orcid Image ;   Naima Samreen Ali4 Author Orcid Image ;   Munmun De Choudhury5 Author Orcid Image ;   Pamela Wisniewski6 Author Orcid Image
Article Authors Cited by Tweetations (1) Metrics

Sarvech Qadir   1 , MSc ;   Ashwaq Alsoubai   2 , PhD ;   Jinkyung Katie Park   3 , PhD ;   Naima Samreen Ali   4 , MSc ;   Munmun De Choudhury   5 , PhD ;   Pamela Wisniewski   6 , PhD

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

2 Department of Information Systems, King Abdulaziz University, Jeddah, Saudi Arabia

3 School of Computing, Clemson University, Clemson, SC, United States

4 School of Information, University of Michigan, Ann Arbor, MI, United States

5 School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, United States

6 International Computer Science Institute, ICSI, Berkeley, CA, United States

Corresponding Author: