Effect of Machine Learning on Risk Stratification for Antiretroviral Treatment Failure in People Living with HIV
This novel model provides an accurate, well-calibrated tool for predicting virologic failure at the individual level, offering valuable clinical utility in optimizing HIV management.
Authors
- Lehao Ren (ORCID: https://orcid.org/0000-0001-9890-6932)
- Hang Ruan (ORCID: https://orcid.org/0000-0001-7506-3805)
- Jisong Yan (ORCID: https://orcid.org/0009-0001-3247-4951)
- Dingyuan Zhao
- Kai Yang (ORCID: https://orcid.org/0009-0006-2227-7803)
- Lianguo Ruan (ORCID: https://orcid.org/0000-0002-7122-1033)
- Wenyuan Zhang (ORCID: https://orcid.org/0000-0001-8041-7129)
- Yu Qi (ORCID: https://orcid.org/0009-0007-0264-4896)
- Shixuan Qi
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Jinyintan Hospital (CN)
- Hubei Provincial Center for Disease Control and Prevention (CN)
- Union Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Infection and Drug Resistance
- Published
- 2025-04-01
- DOI
- https://doi.org/10.2147/idr.s506663
- Citations
- 2
- Primary Topic
- HIV-related health complications and treatments
- Type
- article
- Field-Weighted Citation Impact
- 4.51