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

Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Machine Learning (1465) Infectious Diseases (non-STD/STI) (1575)

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 (2) 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 2024 View