Peer-Reviewed Publication
Trop Med Health2026;54(1)June 13, 2026Journal Article
Predicting unfavorable tuberculosis outcomes using machine learning: a prospective cohort.
Taehyung Lee1, Inseo Choi2, Hoyoun Lee3, Hyung Woo Kim4, Eung Gu Lee5, Yeonhee Park6, Sung Soo Jung7, Jin Woo Kim8, Jee Youn Oh9, Heayon Lee10, Seung Hoon Kim11, Sun-Hyung Kim12, Jiwon Lyu13, Sun Jung Kwon14, Yun-Jeong Jeong15, Hyeon-Kyoung Koo16, Ju Sang Kim4, Jinsoo Min17
1Medical Service Division, Korea Army Training Center, Nonsan, Republic of Korea.
2College of Medicine, Chosun University, Gwangju, Republic of Korea.
3Artificial Intelligence Research Center, JLK Inc., Seoul, Republic of Korea.
4Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
5Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
6Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
7Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Chungnam National University Hospital, Daejeon, Republic of Korea.
8Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
9Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
10Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
11Division of Pulmonology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
12Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Chungbuk National University Hospital, Cheongju, Republic of Korea.
13Department of Pulmonary and Critical Care Medicine, Soonchunhyang University Cheonan Hospital, Soonchunhyang University College of Medicine, Cheonan, Republic of Korea.
14Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Konyang University Hospital, Konyang University College of Medicine, Daejeon, Republic of Korea.
15Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Dongguk University Ilsan Hospital, Goyang, Republic of Korea.
16Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Republic of Korea.
17Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. minjinsoo@catholic.ac.kr.
Abstract
BACKGROUND: Tuberculosis (TB) continues to be a primary cause of mortality from a singular infectious agent worldwide, with a significant number of patients still encountering unfavorable outcomes such as treatment failure, relapse, or death. Early identification of high-risk individuals is essential for optimizing clinical management, yet conventional statistical approaches often fail to capture…
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