Predictive Modeling of HIV Diagnosis Rates Using Machine Learning Techniques

Jarupula, Rahul; Bichindaritz, Isabelle

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Predictive Modeling of HIV Diagnosis Rates Using Machine Learning Techniques

Jarupula, Rahul; Bichindaritz, Isabelle

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Bichindaritz, Isabelle

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2025

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In this study, a machine learning model is developed to predict HIV diagnosis rates based on demographic and geographic factors. Regression methods, including Linear Regression, Random Forest, and XGBoost, are used to assess data on age, gender, race, state, and county. The findings back up focused measures to reduce transmission and the distribution of resources in public health campaigns.

Predictive Modeling of HIV Diagnosis Rates Using Machine Learning Techniques

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