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
BackgroundRisky 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. ObjectiveWe aim to establish...
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| Main Authors: | , , , |
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| Format: | Book |
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JMIR Publications,
2023-01-01T00:00:00Z.
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |