Published on in Vol 24, No 8 (2022): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37850, first published .
Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study

Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study

Web-Based Risk Prediction Tool for an Individual's Risk of HIV and Sexually Transmitted Infections Using Machine Learning Algorithms: Development and External Validation Study

Journals

  1. Florensa D, Mateo-Fornes J, Lopez Sorribes S, Torres Tuca A, Solsona F, Godoy P. Exploring Cancer Incidence, Risk Factors, and Mortality in the Lleida Region: Interactive, Open-source R Shiny Application for Cancer Data Analysis. JMIR Cancer 2023;9:e44695 View
  2. Latt P, Soe N, Xu X, Rahman R, Chow E, Ong J, Fairley C, Zhang L. Assessing disparity in the distribution of HIV and sexually transmitted infections in Australia: a retrospective cross-sectional study using Gini coefficients. BMJ Public Health 2023;1(1):e000012 View
  3. Hu M, Peng H, Zhang X, Wang L, Ren J. Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data. BMC Medical Informatics and Decision Making 2024;24(1) View
  4. Latt P, Soe N, Fairley C, Xu X, King A, Rahman R, Ong J, Phillips T, Zhang L. Assessing the effectiveness of HIV/STI risk communication displays among Melbourne Sexual Health Centre attendees: a cross-sectional, observational and vignette-based study. Sexually Transmitted Infections 2024;100(3):158 View
  5. Latt P, Soe N, Xu X, Ong J, Chow E, Fairley C, Zhang L. Identifying Individuals at High Risk for HIV and Sexually Transmitted Infections With an Artificial Intelligence–Based Risk Assessment Tool. Open Forum Infectious Diseases 2024;11(3) View
  6. Soe N, Latt P, Yu Z, Lee D, Kim C, Tran D, Ong J, Ge Z, Fairley C, Zhang L. Clinical features-based machine learning models to separate sexually transmitted infections from other skin diagnoses. Journal of Infection 2024;88(4):106128 View
  7. Nguyen T, Yang W, Tang Z, Xia X, Mullens A, Dean J, Li Y. Lightweight federated learning for STIs/HIV prediction. Scientific Reports 2024;14(1) View
  8. Ge Q, Lu X, Jiang R, Zhang Y, Zhuang X. Data mining and machine learning in HIV infection risk research: An overview and recommendations. Artificial Intelligence in Medicine 2024;153:102887 View
  9. Liu C, Wu H, Li K, Chi Y, Wu Z, Xing C. Identification of biomarkers for abdominal aortic aneurysm in Behçet's disease via mendelian randomization and integrated bioinformatics analyses. Journal of Cellular and Molecular Medicine 2024;28(10) View
  10. Soe N, Yu Z, Latt P, Lee D, Ong J, Ge Z, Fairley C, Zhang L. Evaluation of artificial intelligence-powered screening for sexually transmitted infections-related skin lesions using clinical images and metadata. BMC Medicine 2024;22(1) View
  11. Jaiteh M, Phalane E, Shiferaw Y, Voet K, Phaswana-Mafuya R. Utilization of Machine Learning Algorithms for the Strengthening of HIV Testing: A Systematic Review. Algorithms 2024;17(8):362 View
  12. Han R, Fan X, Ren S, Niu X. Artificial intelligence in assisting pathogenic microorganism diagnosis and treatment: a review of infectious skin diseases. Frontiers in Microbiology 2024;15 View
  13. King A, Latt P, Soe N, Temple-Smith M, Fairley C, Chow E, Phillips T. User experiences of an AI application for predicting risk of sexually transmitted infections. DIGITAL HEALTH 2024;10 View

Books/Policy Documents

  1. Zar A, Zar L, Mohsen S, Magdi Y, Zughaier S. Surveillance, Prevention, and Control of Infectious Diseases. View