1.
AIDS
; 38(1): 125-127, 2024 01 01.
Artigo
em Inglês
| MEDLINE
| ID: mdl-38061023
RESUMO
Identifying barriers to retention in care (RIC) is critical to ending the HIV epidemic in the United States. Therefore, we developed a machine learning model (MLM) to identify predictive factors for RIC in an urban HIV clinic. Our MLM yielded a positive predictive value of 84%, higher than previously reported MLMs. We found that MLM can be used to develop interventional strategies to enhance RIC in HIV care.