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Predicting Risky Sexual Behavior Among College Students Through Machine Learning Approaches: Cross-sectional Analysis of Individual Data From 1264 Universities in 31 Provinces in China

BACKGROUND: Risky sexual behavior (RSB), the most direct risk factor for sexually transmitted infections (STIs), is common among college students. Thus, identifying relevant risk factors and predicting RSB are important to intervene and prevent RSB among college students. OBJECTIVE: We aim to establ...

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Detalles Bibliográficos
Autores principales:	Li, Xuan, Zhang, Hanxiyue, Zhao, Shuangyu, Tang, Kun
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	JMIR Publications 2023
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9909517/ https://www.ncbi.nlm.nih.gov/pubmed/36696166 http://dx.doi.org/10.2196/41162

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