Detection of Suicidal Ideation in Clinical Interviews for Depression Using Natural Language Processing and Machine Learning: Cross-Sectional Study.
Tim M H LiJie ChenFramenia O C LawChun-Tung LiRachel Ngan Yin ChanJoey Wing Yan ChanSteven Wai-Ho ChauYaping LiuShirley Xin LiJi-Hui ZhangKwong-Sak LeungYun-Kwok WingPublished in: JMIR medical informatics (2023)
This study examined the perspective of using NLP and ML to analyze the texts from clinical interviews for suicidality detection, which has the potential to provide more accurate and specific markers for suicidal ideation detection. The findings may pave the way for developing high-performance assessment of suicide risk for automated detection, including online chatbot-based interviews for universal screening.