Predicting the immunological nonresponse to antiretroviral therapy in people living with HIV: a machine learning-based multicenter large-scale study
This study introduces the random forest model to predict incomplete immune reconstitution in PLWH, which can significantly assist clinicians in the early prediction and intervention of INR among PLWH.
Authors
- Yuanhui Jiang
- Zhe Qian (ORCID: https://orcid.org/0000-0002-2122-325X)
- Shaohang Cai (ORCID: https://orcid.org/0000-0003-3765-9127)
- Mengying Tao (ORCID: https://orcid.org/0000-0002-6036-7133)
- Jianning Mao
- Suling Chen
- Guangyu Liang
- Lixia Zhang (ORCID: https://orcid.org/0000-0002-9653-2735)
- Jie Peng (ORCID: https://orcid.org/0000-0003-0928-3134)
- Xiaoqing Gao (ORCID: https://orcid.org/0000-0003-2000-6269)
Institutions
- Zunyi Medical University (CN)
- Nanfang Hospital (CN)
- Guangdong Academy of Medical Sciences (CN)
- Guangdong Provincial People's Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- Frontiers in Cellular and Infection Microbiology
- Published
- 2025-03-11
- DOI
- https://doi.org/10.3389/fcimb.2025.1466655
- Citations
- 2
- Primary Topic
- HIV/AIDS Research and Interventions
- Type
- article
- Field-Weighted Citation Impact
- 2.79
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China