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Kounseok Lee

Showing results (1-10 of 51) with videos related to

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Journal of Affective Disorders|April 7, 2022
Prediction of suicidal ideation in shift workers compared to non-shift workers using machine learning techniquesHwanjin Park, Kounseok Lee
Journal of Affective Disorders|June 17, 2021
The relationship between metabolically healthy obesity and suicidal ideationHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|April 23, 2022
The Effectiveness of Predicting Suicidal Ideation through Depressive Symptoms and Social Isolation Using Machine Learning TechniquesSunhae Kim, Kounseok Lee
Psychiatry Research|January 14, 2024
Association between insurance type and suicide-related behavior among US adults: The impact of the Affordable Care ActSeungwon Cho, Kounseok Lee
Psychiatry Research|August 27, 2025
Machine learning-based prediction of suicide risk using adult attention-deficit/hyperactivity disorder symptoms and depression indicators: insights from a nationally representative south korean surveySunhae Kim, Kounseok Lee
Psychology Research and Behavior Management|September 20, 2022
Association Between Breakfast Consumption and Suicidal Attempts in AdolescentsHwanjin Park, Kounseok Lee
Neuropsychiatric Disease and Treatment|December 1, 2021
Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning MethodsSunhae Kim, Kounseok Lee
Journal of Personalized Medicine|September 23, 2022
Using Boosted Machine Learning to Predict Suicidal Ideation by Socioeconomic Status among AdolescentsHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|June 24, 2022
A Machine Learning Approach for Predicting Wage Workers' Suicidal IdeationHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|May 28, 2022
A Network Analysis of Depressive Symptoms in the Elderly with Subjective Memory ComplaintsSunhae Kim, Kounseok Lee
Pageof 6

Showing results (1-10 of 51) with videos related to

Sort By:
Pageof 6
Journal of Affective Disorders|April 7, 2022
Prediction of suicidal ideation in shift workers compared to non-shift workers using machine learning techniquesHwanjin Park, Kounseok Lee
Journal of Affective Disorders|June 17, 2021
The relationship between metabolically healthy obesity and suicidal ideationHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|April 23, 2022
The Effectiveness of Predicting Suicidal Ideation through Depressive Symptoms and Social Isolation Using Machine Learning TechniquesSunhae Kim, Kounseok Lee
Psychiatry Research|January 14, 2024
Association between insurance type and suicide-related behavior among US adults: The impact of the Affordable Care ActSeungwon Cho, Kounseok Lee
Psychiatry Research|August 27, 2025
Machine learning-based prediction of suicide risk using adult attention-deficit/hyperactivity disorder symptoms and depression indicators: insights from a nationally representative south korean surveySunhae Kim, Kounseok Lee
Psychology Research and Behavior Management|September 20, 2022
Association Between Breakfast Consumption and Suicidal Attempts in AdolescentsHwanjin Park, Kounseok Lee
Neuropsychiatric Disease and Treatment|December 1, 2021
Screening for Depression in Mobile Devices Using Patient Health Questionnaire-9 (PHQ-9) Data: A Diagnostic Meta-Analysis via Machine Learning MethodsSunhae Kim, Kounseok Lee
Journal of Personalized Medicine|September 23, 2022
Using Boosted Machine Learning to Predict Suicidal Ideation by Socioeconomic Status among AdolescentsHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|June 24, 2022
A Machine Learning Approach for Predicting Wage Workers' Suicidal IdeationHwanjin Park, Kounseok Lee
Journal of Personalized Medicine|May 28, 2022
A Network Analysis of Depressive Symptoms in the Elderly with Subjective Memory ComplaintsSunhae Kim, Kounseok Lee
Pageof 6