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

Natural Language Processing (650) Clinical Information and Decision Making (1340) Machine Learning (1401) Depression and Mood Disorders; Suicide Prevention (1290) Diagnostic Tools in Mental Health (224) Intentional Self-Harm (91) Clinical Information and Decision Making (1340) e-Mental Health and Cyberpsychology (1411) Machine Learning (1401) Depression and Mood Disorders; Suicide Prevention (1290) e-Mental Health and Cyberpsychology (1411) Intentional Self-Harm (91) Diagnostic Tools in Mental Health (224)

Published on in Vol 11 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50221, first published .
Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study

Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study

Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study

Authors of this article:

Tim M H Li1 Author Orcid Image ;   Jie Chen1 Author Orcid Image ;   Framenia O C Law1 Author Orcid Image ;   Chun-Tung Li1 Author Orcid Image ;   Ngan Yin Chan1 Author Orcid Image ;   Joey W Y Chan1 Author Orcid Image ;   Steven W H Chau1 Author Orcid Image ;   Yaping Liu1 Author Orcid Image ;   Shirley Xin Li2, 3 Author Orcid Image ;   Jihui Zhang1, 4 Author Orcid Image ;   Kwong-Sak Leung5, 6 Author Orcid Image ;   Yun-Kwok Wing1 Author Orcid Image
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