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Prediction of Suicidal Ideation among Korean Adults Using Machine Learning: A Cross-Sectional Study
Bumjo Oh, Je-Yeon Yun, Eun Chong Yeo, Dong-Hoi Kim, Jin Kim, Bum-Joo Cho
Psychiatry Investig. 2020;17(4):331-340. Published online 2020 Mar 27 DOI: https://doi.org/10.30773/pi.2019.0270
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Development and Effectiveness of a Clinical Decision Support System for Pressure Ulcer Prevention Care Using Machine Learning
Myoung Soo Kim, Jung Mi Ryu, Byung Kwan Choi
CIN: Computers, Informatics, Nursing.2023; 41(4): 236. CrossRef Factors Related to Suicidal Ideation by Gender and Age Group in Korean Adults
Eun Young Kim, Yong Whi Jeong, Jihye Lim, Dae Ryong Kang
Journal of Korean Medical Science.2023;[Epub] CrossRef Machine learning for suicidal ideation identification: A systematic literature review
Wesllei Felipe Heckler, Juliano Varella de Carvalho, Jorge Luis Victória Barbosa
Computers in Human Behavior.2022; 128: 107095. CrossRef Use of Artificial Intelligence-Based Strategies for Assessing Suicidal Behavior and Mental Illness: A Literature Review
Nighat Z Khan, Muhammad Ali Javed
Cureus.2022;[Epub] CrossRef Suicidal behaviour prediction models using machine learning techniques: A systematic review
Noratikah Nordin, Zurinahni Zainol, Mohd Halim Mohd Noor, Lai Fong Chan
Artificial Intelligence in Medicine.2022; 132: 102395. CrossRef Use of Artificial Intelligence-Based Strategies for Assessing Suicidal Behavior and Mental Illness – A Literature Review
Nighat Z. Khan, Muhammad Ali Javed
SSRN Electronic Journal .2022;[Epub] CrossRef
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