@文章{信息:doi/10.2196/37850，作者="徐祥龙和余，真和葛，宗元和周，Eric P F和包，伊宁和Ong, Jason J和李，Wei和Wu, Jinrong和Fairley, Christopher K和张磊"，标题="基于网络的基于机器学习算法的个体HIV和性传播感染风险预测工具:，期刊=“J Med Internet Res”，年=“2022”，月=“8”，日=“25”，卷=“24”，数=“8”，页数=“e37850”，关键词=“HIV;性传播感染;梅毒;淋病;衣原体;性的健康;性传播;性传播;预测; web-based; risk assessment; machine learning; model; algorithm; predictive; risk; development; validation", abstract="Background: HIV and sexually transmitted infections (STIs) are major global public health concerns. Over 1 million curable STIs occur every day among people aged 15 years to 49 years worldwide. Insufficient testing or screening substantially impedes the elimination of HIV and STI transmission. Objective: The aim of our study was to develop an HIV and STI risk prediction tool using machine learning algorithms. Methods: We used clinic consultations that tested for HIV and STIs at the Melbourne Sexual Health Centre between March 2, 2015, and December 31, 2018, as the development data set (training and testing data set). We also used 2 external validation data sets, including data from 2019 as external ``validation data 1'' and data from January 2020 and January 2021 as external ``validation data 2.'' We developed 34 machine learning models to assess the risk of acquiring HIV, syphilis, gonorrhea, and chlamydia. We created an online tool to generate an individual's risk of HIV or an STI. Results: The important predictors for HIV and STI risk were gender, age, men who reported having sex with men, number of casual sexual partners, and condom use. Our machine learning--based risk prediction tool, named MySTIRisk, performed at an acceptable or excellent level on testing data sets (area under the curve [AUC] for HIV=0.78; AUC for syphilis=0.84; AUC for gonorrhea=0.78; AUC for chlamydia=0.70) and had stable performance on both external validation data from 2019 (AUC for HIV=0.79; AUC for syphilis=0.85; AUC for gonorrhea=0.81; AUC for chlamydia=0.69) and data from 2020-2021 (AUC for HIV=0.71; AUC for syphilis=0.84; AUC for gonorrhea=0.79; AUC for chlamydia=0.69). Conclusions: Our web-based risk prediction tool could accurately predict the risk of HIV and STIs for clinic attendees using simple self-reported questions. MySTIRisk could serve as an HIV and STI screening tool on clinic websites or digital health platforms to encourage individuals at risk of HIV or an STI to be tested or start HIV pre-exposure prophylaxis. The public can use this tool to assess their risk and then decide if they would attend a clinic for testing. Clinicians or public health workers can use this tool to identify high-risk individuals for further interventions. ", issn="1438-8871", doi="10.2196/37850", url="//www.mybigtv.com/2022/8/e37850", url="https://doi.org/10.2196/37850", url="http://www.ncbi.nlm.nih.gov/pubmed/36006685" }