Psychiatry Investigation

Exploring Informative Items for Bipolar Disorder Classification Using Machine Learning With Anger Coping Styles in Combination With the Mood Disorder Questionnaire and Bipolar Spectrum Diagnostic Scale: Kyungwon Kim, Eunsoo Moon, Hyunju Lim, Hyunji Lee, Hwagyu Suh, Young Min Lee, Byung Dae Lee; Psychiatry Investig. 2025;22(12):1430-1441. Published online December 4, 2025; DOI: https://doi.org/10.30773/pi.2025.0108; Full text PubReader ePub PDF

Optimizing Suicide Risk Prediction in Korea: A Comparison of Model Performance Using Resampling Methods and Machine Learning Algorithms: Eunji Lim, Bong-Jo Kim, Boseok Cha, So-Jin Lee, Jae-Won Choi, Nuree Kang, Soyoung Park, Sung Hyo Seo, Dongyun Lee; Psychiatry Investig. 2025;22(11):1309-1318. Published online November 12, 2025; DOI: https://doi.org/10.30773/pi.2025.0187; Full text PubReader ePub PDF Supplementary Materials

Predicting Efficacy of Virtual Reality-Based Stabilization for Individuals With Posttraumatic Stress Symptoms: A Machine Learning Approach: Yongmin Shin, Euijin Kim, Kibum Kim, Ji Sun Kim, Sungkean Kim, Bin-Na Kim; Psychiatry Investig. 2025;22(10):1178-1190. Published online October 2, 2025; DOI: https://doi.org/10.30773/pi.2025.0168; Full text PubReader ePub PDF Supplementary Materials

Contribution of Chronic Disease in Predicting Depression and Suicidal Ideation Among the Older Adult Population: Youngbin Seo, Hae-Young Kim, KiBong Choi, Sunmi Song, Junesun Kim; Psychiatry Investig. 2025;22(9):1068-1076. Published online August 21, 2025; DOI: https://doi.org/10.30773/pi.2024.0106; Full text PubReader ePub PDF Supplementary Materials

Predicting 5-Year Survival and Mortality in Dementia Patients: A Data-Driven Approach Using XGBoost for Enhanced Care and Resource Allocation: Yi-Guang Wang, Hsin-An Chang, Mu-Hong Chen, Nian-Sheng Tzeng, Jin Narumoto, Chih-Sung Liang, Ta-Chuan Yeh; Psychiatry Investig. 2025;22(9):1057-1067. Published online September 1, 2025; DOI: https://doi.org/10.30773/pi.2024.0351; Full text PubReader ePub PDF

Enhancing Electroencephalogram-Based Prediction of Posttraumatic Stress Disorder Treatment Response Using Data Augmentation: Sangha Kim, Chaeyeon Yang, Suh-Yeon Dong, Seung-Hwan Lee; Psychiatry Investig. 2025;22(8):914-920. Published online August 5, 2025; DOI: https://doi.org/10.30773/pi.2025.0133; Full text PubReader ePub PDF

Machine Learning Prediction of Attachment Type From Bio-Psychological Factors in Patients With Depression: Yoon Jae Cho, Jin Sun Ryu, Jeong-Ho Seok, Eunjoo Kim, Jooyoung Oh, Byung-Hoon Kim; Psychiatry Investig. 2025;22(4):412-423. Published online April 11, 2025; DOI: https://doi.org/10.30773/pi.2024.0392
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The Clinical Utility of Biomarkers in Diagnosing Major Depressive Disorder in Adults: A Systematic Review of Literature From 2013 to 2023: Shi-han Ang, Roger C. Ho, Roger S. McIntyre, Zhisong Zhang, Soon-kiat Chang, Kayla M. Teopiz, Cyrus SH Ho; Psychiatry Investig. 2025;22(4):341-356. Published online April 11, 2025; DOI: https://doi.org/10.30773/pi.2024.0152
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Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study: Xing-Xuan Dong, Jian-Hua Liu, Tian-Yang Zhang, Chen-Wei Pan, Chun-Hua Zhao, Yi-Bo Wu, Dan-Dan Chen; Psychiatry Investig. 2025;22(3):267-278. Published online March 18, 2025; DOI: https://doi.org/10.30773/pi.2024.0156
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Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old: Kwang-Sig Lee, Byung-Joo Ham; Psychiatry Investig. 2024;21(12):1382-1390. Published online December 23, 2024; DOI: https://doi.org/10.30773/pi.2024.0249
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Novel Deep Learning-Based Vocal Biomarkers for Stress Detection in Koreans: Junghyun Namkung, Seok Min Kim, Won Ik Cho, So Young Yoo, Beomjun Min, Sang Yool Lee, Ji-Hye Lee, Heyeon Park, Soyoung Baik, Je-Yeon Yun, Nam Soo Kim, Jeong-Hyun Kim; Psychiatry Investig. 2024;21(11):1228-1237. Published online November 18, 2024; DOI: https://doi.org/10.30773/pi.2024.0131
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Using Deep Learning Techniques as an Attempt to Create the Most Cost-Effective Screening Tool for Cognitive Decline: Hye-Geum Kim, Wan-Seok Seo, Bon-Hoon Koo, Eun-Jin Cheon, Seokho Yun, Sohye Jo, Byoungyoung Gu; Psychiatry Investig. 2024;21(8):912-917. Published online August 2, 2024; DOI: https://doi.org/10.30773/pi.2024.0157; Full text PubReader ePub PDF

Simultaneous Utilization of Mood Disorder Questionnaire and Bipolar Spectrum Diagnostic Scale for Machine Learning-Based Classification of Patients With Bipolar Disorders and Depressive Disorders: Kyungwon Kim, Hyun Ju Lim, Je-Min Park, Byung-Dae Lee, Young-Min Lee, Hwagyu Suh, Eunsoo Moon; Psychiatry Investig. 2024;21(8):877-884. Published online August 2, 2024; DOI: https://doi.org/10.30773/pi.2023.0361
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Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks: Jin-Hyuck Park; Psychiatry Investig. 2024;21(3):294-299. Published online March 25, 2024; DOI: https://doi.org/10.30773/pi.2023.0409
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A Case-Control Clinical Trial on a Deep Learning-Based Classification System for Diagnosis of Amyloid-Positive Alzheimer’s Disease: Jong Bin Bae, Subin Lee, Hyunwoo Oh, Jinkyeong Sung, Dongsoo Lee, Ji Won Han, Jun Sung Kim, Jae Hyoung Kim, Sang Eun Kim, Ki Woong Kim; Psychiatry Investig. 2023;20(12):1195-1203. Published online December 18, 2023; DOI: https://doi.org/10.30773/pi.2023.0052
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