皮肤性病诊疗学杂志2025，Vol.32Issue(9)：673-678,6.DOI:10.3969/j.issn.1674-8468.2025.09.010
基于机器学习的HIV和性传播感染风险评估研究进展
Research progress on machine learning-based risk assessment for HIV and sexually trans-mitted infections
摘要
Abstract
HIV and sexually transmitted infections(STIs)are critical global public health is-sues.In resource-constrained settings,the accurate identification of high-risk populations is criti-cal for the effective prevention of HIV/STI transmission.As a pivotal subset of artificial intelli-gence,machine learning offers advanced capabilities in data processing and pattern recognition,providing novel approaches for risk assessment in HIV/STIs,and is an emerging focus of research in this field.This review summarizes recent advances in machine learning for assessing the risk of HIV/STI infections,with a focus on comparing the strengths and limitations of different algo-rithms.It provides an in-depth analysis of the main risk factors among various high-risk popula-tions and discusses the shortcomings and challenges of current research regarding sample represen-tativeness,model interpretability,and integration with intervention strategies.The aim is to pro-vide rational and practical guidance for future research.关键词
性传播感染/HIV/机器学习/风险评估Key words
sexually transmitted infections/HIV/machine learning/risk assessment引用本文复制引用
王劲燊,李海逸,梁鹏,阿力克斯·木合亚提,黄澍杰,赵培祯,王成..基于机器学习的HIV和性传播感染风险评估研究进展[J].皮肤性病诊疗学杂志,2025,32(9):673-678,6.基金项目
广东省医学科研基金(B2025372) （B2025372）
广州市科技计划项目(2024A04J4485) （2024A04J4485）
