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

Applications of AI (246) Artificial Intelligence (1996) Ethical, Legal, and Social Issues in AI (91) Ethics, Privacy, and Legal Issues (592) Equity and Digital Divide (333) Demographics of Users, Social & Digital Divide (886) Systemic Racism and Racial Bias in Health Care and Society (120)

Published on in Vol 3 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58275, first published .
Ensuring Appropriate Representation in Artificial Intelligence–Generated Medical Imagery: Protocol for a Methodological Approach to Address Skin Tone Bias

Ensuring Appropriate Representation in Artificial Intelligence–Generated Medical Imagery: Protocol for a Methodological Approach to Address Skin Tone Bias

Ensuring Appropriate Representation in Artificial Intelligence–Generated Medical Imagery: Protocol for a Methodological Approach to Address Skin Tone Bias

Authors of this article:

Andrew O'Malley1 Author Orcid Image ;   Miriam Veenhuizen1 Author Orcid Image ;   Ayla Ahmed1 Author Orcid Image
Article Authors Cited by (6) Tweetations (5) Metrics Author Video

Journals

  1. Ahmed A, Kerr E, O’Malley A. Quality assurance and validity of AI-generated single best answer questions. BMC Medical Education 2025;25(1) View
  2. Haider S, Prabha S, Gomez-Cabello C, Borna S, Pressman S, Genovese A, Trabilsy M, Galvao A, Aziz K, Murray P, Parte Y, Yu Y, Tao C, Forte A. A Validity Analysis of Text-to-Image Generative Artificial Intelligence Models for Craniofacial Anatomy Illustration. Journal of Clinical Medicine 2025;14(7):2136 View
  3. Lederman O, Llana A, Murray J, Stanton R, Chugh R, Haywood D, Burdett A, Warman G, Walker J, Hart N. Promises and perils of generative artificial intelligence: a narrative review informing its ethical and practical applications in clinical exercise physiology. BMC Sports Science, Medicine and Rehabilitation 2025;17(1) View
  4. M'gadzah S, O'Malley A. Enhancing Diagnostic Accuracy of Ophthalmological Conditions With Complex Prompts in GPT-4: Comparative Analysis of Global and Low- and Middle-Income Country (LMIC)–Specific Pathologies. JMIR Formative Research 2025;9:e64986 View
  5. Mainardi V, Canto M, Melillo T, Lorenzini N, Bagnoni G, Moccia S, Ciuti G. A Thermal-Imaging System and Machine-Learning Classification Algorithm for Skin Cancer Screening. IEEE Transactions on Medical Robotics and Bionics 2025;7(3):938 View
  6. Kumar R, Kim Y, Byun Y. Hybrid Framework Combining Diffusion-Based Image Augmentation and Feature Level SMOTE for Addressing Extreme Class Imbalance. IEEE Access 2025;13:154623 View