HIV/AIDS remains a critical global public health concern.In recent years,the increasingly burgeoning application of artificial intelligence(AI)in the field of healthcare has prompted new research avenues into how AI can improve the quality and efficiency of HIV prevention and treatment,and better address the challenges of HIV.Machine learning,a significant branch of AI,has been employed in numerous studies to explore its potential in developing HIV prevention and treatment strategies.This involves using various machine learning algorithms to construct models based on data such as demographics,clinical indicators,behavioral characteristics,and other datasets,with the aim of optimizing HIV prevention and treatment strategies.Machine learning models based on data-driven modeling capabilities surpass those of traditional methods in terms of efficiency and precision,demonstrating their unique advantages and efficacy.This review summarizes the advances in studies on the applications of machine learning for HIV prevention and treatment.
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