ArticleJournal of the American Medical Informatics Association : JAMIA2022
Towards gender equity in artificial intelligence and machine learning applications in dermatology.
Article in Journal of the American Medical Informatics Association : JAMIA, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Attention guided fair artificial intelligence modeling for skin cancer diagnosis.NPJ digital medicine · 2026Article
- Article
- Evaluating an Artificial Intelligence software for opportunistic low bone mineral density and osteoporosis screening: a validation study.JBMR plus · 2026Article
- Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members.Journal of medical Internet research · 2025Article
- Status and perceptions of ChatGPT utilization among medical students: a survey-based study.BMC medical education · 2025Article
- Harnessing artificial intelligence for enhanced public health surveillance: a narrative review.Frontiers in public health · 2025Review
- Transgender Individuals' Perspectives on Teledermatology-Based Acne Research.Archives of dermatological research · 2025Article
- Human-centered AI as a framework guiding the development of image-based diagnostic tools in oncology: a systematic review.ESMO real world data and digital oncology · 2024Review
- Towards equitable AI in oncology.Nature reviews. Clinical oncology · 2024Review
- Digital Determinants of Health: Health data poverty amplifies existing health disparities-A scoping review.PLOS digital health · 2023Article
- Equity within AI systems: What can health leaders expect?Healthcare management forum · 2023Article
- Visceral fat and attribute-based medicine in chronic kidney disease.Frontiers in endocrinology · 2023Review
- The Impact of Artificial Intelligence on Health Equity in Oncology: Scoping Review.Journal of medical Internet research · 2022Article
- Informatics for sex- and gender-related health: understanding the problems, developing new methods, and designing new solutions.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Consequences of inequity in the neurosurgical workforce: Lessons from traumatic brain injury.Frontiers in surgery · 2022Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There has been increased excitement around the use of machine learning (ML) and artificial intelligence (AI) in dermatology for the diagnosis of skin cancers and assessment of other dermatologic conditions. As these technologies continue to expand, it is essential to ensure they do not create or widen sex- and gender-based disparities in care. While desirable bias may result from the explicit inclusion of sex or gender in diagnostic criteria of diseases with gender-based differences, undesirable biases can result from usage of datasets with an underrepresentation of certain groups. We believe that sex and gender differences should be taken into consideration in ML/AI algorithms in dermatology because there are important differences in the epidemiology and clinical presentation of dermatologic conditions including skin cancers, sex-specific cancers, and autoimmune conditions. We present recommendations for ensuring sex and gender equity in the development of ML/AI tools in dermatology to increase desirable bias and avoid undesirable bias.
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Registered trials
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