Volta

Early prediction of immunological non-responders in people living with HIV using machine learning: Model development and validation in multicenter cohorts in China

BACKGROUND: T cells, known as immune non-responders (INR), associated with poor clinical outcomes. Due to the complex pathogenesis and the absence of effective treatments, early prediction and intervention of INR are critical. With the rapid advancements in artificial intelligence, particularly in machine learning (ML), developing an interpretable ML model to identify individuals at high risk of INR can facilitate personalized treatment strategies and improve clinical management. METHODS: This retrospective study was conducted from a long-term multicenter cohort involving 30938 PLWH attending three hospitals from January 2003 to December 2023. Seven ML algorithms were employed to construct prediction models. The area under the receiver operating characteristic curve (AUC), precision-recall curves, calibration plots, clinical impact curves, and decision curve analysis were used …

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