Prediction of new HIV infection in men who have sex with men based on machine learning: secondary analysis of a prospective cohort study from Western China.

ABSTRACT:

Objective

This study aimed to construct a model based on machine learning to predict new HIV infections in HIV-negative men who have sex with men (MSM).

Methods

This is a secondary analysis of a previous random clinical trial aiming to evaluate the preventive effects of PrEP on new HIV infection in MSM. During 2013-2015, 1455 HIV-negative MSM were enrolled. Participants were divided into treatment group and control group and regularly followed up until they seroconverted to HIV positive or until the 2-year endpoint reached. Five machine-learning approaches were applied to predict the risk of HIV infection. Model performance was evaluated using Harrel's C-index and area under the receiver operator characteristic curve (AUC) and validated in an external validation cohort. To e

SUBMITTER: Li K 

PROVIDER: S-EPMC11894746 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature