Predicting unfavorable tuberculosis outcomes using machine learning: a prospective cohort
Taehyung Lee, Inseo Choi, Hoyoun Lee, Hyung Woo Kim, Eung Gu Lee, Yeonhee Park, Sung Soo Jung, Jin Woo Kim, Jee Youn Oh, Heayon Lee, Seung Hoon Kim, Sun-Hyung Kim, Jiwon Lyu, Sun Jung Kwon, Yun-Jeong Jeong, Hyeon-Kyoung Koo, Ju Sang Kim, Jinsoo Min · 2026
Read Predicting unfavorable tuberculosis outcomes using machine learning: a prospective cohort by Taehyung Lee, Inseo Choi, Hoyoun Lee, Hyung Woo Kim, Eung Gu Lee, Yeonhee Park, Sung Soo Jung, Jin Woo Kim, Jee Youn Oh, Heayon Lee, Seung Hoon Kim, Sun-Hyung Kim, Jiwon Lyu, Sun Jung Kwon, Yun-Jeong Jeong, Hyeon-Kyoung Koo, Ju Sang Kim, Jinsoo Min (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13274168.txt.
Description
Taehyung Lee and a large team report a 2026 journal article using machine learning to predict bad outcomes in tuberculosis care. Tuberculosis still kills many patients through treatment failure, relapse, or death, yet spotting the highest-risk patients early is hard. The team built its models on a prospective Korean cohort gathered from 2016 to 2024.
Among 1,580 patients, 109, or about seven percent, had an unfavorable outcome. The best model, called XGBoost, scored well at ranking risk and caught about seventy-three percent of bad outcomes by flagging just the riskiest fifth of patients. Blood albumin, hemoglobin, white-cell counts, and age mattered most. Dropping lab data clearly weakened the model.
Catalog record
| CREATOR | Taehyung Lee, Inseo Choi, Hoyoun Lee, Hyung Woo Kim, Eung Gu Lee, Yeonhee Park, Sung Soo Jung, Jin Woo Kim, Jee Youn Oh, Heayon Lee, Seung Hoon Kim, Sun-Hyung Kim, Jiwon Lyu, Sun Jung Kwon, Yun-Jeong Jeong, Hyeon-Kyoung Koo, Ju Sang Kim, Jinsoo Min |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 44523 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |