This paper is in the following e-collection/theme issue:

Behavioural Surveillance for Public Health (235) Machine Learning (1501) Artificial Intelligence (1421) Online Dating, Sexual Health Behavior (163) Risky Sexual Behavior (147) HIV/AIDS/STI Prevention and Care (882) Prevention and Health Promotion (1015)

Published on in Vol 9 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41162, first published .
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

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

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

Authors of this article:

Xuan Li1 Author Orcid Image ;   Hanxiyue Zhang1 Author Orcid Image ;   Shuangyu Zhao1 Author Orcid Image ;   Kun Tang1 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Tu P, Hu D, Wu S, Li J, Jiang X, Pei K, Zhang W. Characteristics and contraceptive practices among Chinese women seeking abortion: a multicentre, descriptive study from 2019 to 2021. BMJ Sexual & Reproductive Health 2024;50(4):252 View
  2. Yang Z, Chen W, Chen W, Ma Q, Wang H, Jiang T, Fu Y, Zhou X, Mazza M. Factors associated with casual sexual behavior among college students in Zhejiang Province, China: A cross-sectional survey. PLOS ONE 2024;19(7):e0304804 View
  3. Qin Q, Yu H, Zhao J, Xu X, Li Q, Gu W, Guo X. Machine learning-based derivation and validation of three immune phenotypes for risk stratification and prognosis in community-acquired pneumonia: a retrospective cohort study. Frontiers in Immunology 2024;15 View