Generalizable pipeline for constructing HIV risk prediction models across electronic health record systems.

ABSTRACT:

Objective

The HIV epidemic remains a significant public health issue in the United States. HIV risk prediction models could be beneficial for reducing HIV transmission by helping clinicians identify patients at high risk for infection and refer them for testing. This would facilitate initiation on treatment for those unaware of their status and pre-exposure prophylaxis for those uninfected but at high risk. Existing HIV risk prediction algorithms rely on manual construction of features and are limited in their application across diverse electronic health record systems. Furthermore, the accuracy of these models in predicting HIV in females has thus far been limited.

Materials and methods

We devised a pipeline for automatic construction of prediction models based on automatic

SUBMITTER: May SB 

PROVIDER: S-EPMC10873846 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature