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

Artificial Intelligence (2129) Clinical Information and Decision Making (1915) Machine Learning (2076) Infectious Diseases (non-STD/STI) (1726)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52490, first published .
Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study

Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study

Using AI to Differentiate Mpox From Common Skin Lesions in a Sexual Health Clinic: Algorithm Development and Validation Study

Authors of this article:

Nyi Nyi Soe1, 2 Author Orcid Image ;   Zhen Yu1, 3 Author Orcid Image ;   Phyu Mon Latt1, 2 Author Orcid Image ;   David Lee4 Author Orcid Image ;   Ranjit Singh Samra5 Author Orcid Image ;   Zongyuan Ge3 Author Orcid Image ;   Rashidur Rahman4 Author Orcid Image ;   Jiajun Sun1, 2 Author Orcid Image ;   Jason J Ong2, 4 Author Orcid Image ;   Christopher K Fairley2, 4 Author Orcid Image ;   Lei Zhang1, 2, 6 Author Orcid Image
Article Authors Cited by (11) Tweetations (2) Metrics

Journals

  1. 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
  2. Soe N, Latt P, King A, Lee D, Phillips T, Fairley C, Zhang L, Ong J. What Do People Want from an AI-Assisted Screening App for Sexually Transmitted Infection-Related Anogenital Lesions: A Discrete Choice Experiment. The Patient - Patient-Centered Outcomes Research 2025;18(2):131 View
  3. Soe N, Towns J, Latt P, Woodberry O, Chung M, Lee D, Ong J, Chow E, Zhang L, Fairley C. Accuracy of symptom checker for the diagnosis of sexually transmitted infections using machine learning and Bayesian network algorithms. BMC Infectious Diseases 2024;24(1) View
  4. He S, Zhao J, Chen J, Liang J, Hu X, Zhang X, Zeng H, Sun G. Urogenital Manifestations in Mpox (Monkeypox) Infection: A Comprehensive Review of Epidemiology, Pathogenesis, and Therapeutic Approaches. Infection and Drug Resistance 2025;Volume 18:209 View
  5. Ong J, Unemo M, Molina J, Miranda A, Seib K, Brito de Mello M, Doherty M, Johnson C, Delany-Moretlwe S, Fairley C. Beyond behavioural change: prioritising structural solutions to control bacterial sexually transmitted infections. eClinicalMedicine 2025;83:103198 View
  6. Soe N, Latt P, Lee D, Towns J, King A, Chow E, Ong J, Zhang L, Fairley C. Impact of Result Displays in an Anogenital Symptom Checker App on Health-seeking Behaviours: A Cross-sectional, Vignette-based Study. Open Forum Infectious Diseases 2025;12(4) View
  7. Ernest-Okonofua E, Zubairu Z, Oduoye M, Tariq M, Muhammad S, Siddiqua Z, Vuyyuru M, Wafula B, Akhtar R, Fasasi A, Ubechu S, Olayinka B. Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review. Journal of Primary Care & Community Health 2025;16 View
  8. Olawade D, Ezeagu C, Alisi C, Clement David-Olawade A, Eniola D, Akingbala T, Wada O. AI-driven strategies for enhancing Mpox surveillance and response in Africa. Journal of Virological Methods 2026;339:115270 View
  9. Soe N, Kusnandar I, Latt P, Fairley C, Chow E, Maatouk I, Johnson C, Shah P, Peters R, Subissi L, Zhang L, Ong J. Use of AI in Identification of Sexually Transmitted Infections and Anogenital Dermatoses. JAMA Network Open 2025;8(10):e2533512 View
  10. Peters R, Grinsztejn B, Celum C, Mayer K, Molina J, Delany-Moretlwe S, Ngure K, Torres-Rueda S, Guy R, Reiss P, Ferrand R, Kittiyaowamarn R, Bekker L. Innovations in the biomedical prevention, diagnosis, and service delivery of HIV and other sexually transmitted infections. The Lancet 2025;406(10515):2133 View
  11. Soe N, Latt P, Lee D, Yu Z, Schmidt M, Bissessor M, Aung E, Ge Z, Rahman R, Chow E, Ong J, Fairley C, Zhang L. Using deep learning systems for diagnosing common skin lesions in sexual health. Communications Medicine 2025;5(1) View