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Explainable AI-Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study.

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第一作者： Francis,Ngema

第一单位： Centre of Applied Data Science, University of Johannesburg, Johannesburg, South Africa.

作者： Francis,Ngema ^[1] ; Albert,Whata ^[2] ; Micheal O,Olusanya ^[3] ; Siyabonga,Mhlongo ^[4]

作者单位： Centre of Applied Data Science, University of Johannesburg, Johannesburg, South Africa. ^[1] Department of Statistics, University of Pretoria, Pretoria, South Africa. ^[2] Department of Computer Science and Information Technology, Sol Plaatje University, Kimberley, South Africa. ^[3] Department of Applied Information Systems, University of Johannesburg, Johannesburg, South Africa. ^[4]

关键词 HIV viral suppression Uganda XGBoost adherence antiretroviral therapy artificial intelligence clinical decision-making explainable AI extreme gradient boosting machine learning predictive modeling public health

DOI 10.2196/68196

PMID 41358918

发布时间 2026-01-23

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Explainable AI-Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study.

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Explainable AI-Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study.

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