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Risk Prediction of Liver Injury in Pediatric Tuberculosis Treatment: Development of an Automated Machine Learning Model

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成果类型:
期刊论文
作者:
Zeng, Ying;Lu, Hong;Li, Sen;Shi, Qun-Zhi;Liu, Lin;...
通讯作者:
Yan, P
作者机构:
[Lu, Hong; Yan, Pan; Zeng, Ying; Yan, P; Shi, Qun-Zhi; Gong, Yong-Qing; Liu, Lin] Univ South China, Affiliated Changsha Cent Hosp, Hengyang Med Sch, Dept Pharm, Changsha 410004, Peoples R China.
[Li, Sen] Huazhong Univ Sci & Technol, Union Hosp, Tongji Med Coll, Dept Pharm, Wuhan 430030, Peoples R China.
通讯机构:
[Yan, P ] U
Univ South China, Affiliated Changsha Cent Hosp, Hengyang Med Sch, Dept Pharm, Changsha 410004, Peoples R China.
语种:
英文
关键词:
anti-tuberculosis drug-induced liver injury;automatic machine learning;children;gradient boost machine;retrospective study
期刊:
Drug Design, Development and Therapy
ISSN:
1177-8881
年:
2025
卷:
19
页码:
239-250
基金类别:
Changsha Central Hospital Affiliated to University of South China Foundation of key Program [YNKY202305, YNKY202204]; National Natural Science Foundation of China [82003870]; Natural Science Foundation of Changsha [kq2014012]; Scientific Research Project of Education Department of Hunan Province [23B0438]; Scientific and technological innovation project of Hunan Province [2021SK53407]
机构署名:
本校为第一且通讯机构
院系归属:
药学与生物科学学院
摘要:
PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions related to first-line anti-tuberculosis drugs in pediatric tuberculosis patients. This study aims to develop an automatic machine learning (AutoML) model for predicting the risk of anti-tuberculosis drug-induced liver injury (ATB-DILI) in children. METHODS: A retrospective study was performed on the clinical data and therapeutic drug monitoring (TDM) results of children initially treated for tuberculosis at the affiliated Changsha Central Hospital of University of South China. After the featu...

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