{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T15:32:05Z","timestamp":1788535925067,"version":"build-2803163510"},"reference-count":85,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2022,5,17]],"date-time":"2022-05-17T00:00:00Z","timestamp":1652745600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003107","name":"Bundesministerium f\u00fcr Gesundheit","doi-asserted-by":"publisher","award":["2520DAT920"],"award-info":[{"award-number":["2520DAT920"]}],"id":[{"id":"10.13039\/501100003107","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acad Dermatol Venereol"],"published-print":{"date-parts":[[2022,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Visual data are particularly amenable for machine learning techniques. With clinical photography established for skin surveillance and documentation purposes as well as progress checks, dermatology is an ideal field for the development and application of emerging machine learning health care applications (ML\u2010HCAs). To date, several ML\u2010HCAs have detected malignant skin lesions on par with experts or found overlooked visual patterns that correlate with certain dermatological diseases. However, it is well established that ML\u2010HCAs come with ethical and social implications.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>Currently, there is a lack of research that establishes model design, training, usage and regulation of such technologies sufficient to ensure ethically and socially responsible development and clinical translation, specifically within the field of dermatology. With this paper, we aim to give an overview of currently discussed ethical issues relating to dermatological ML\u2010HCAs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>On the basis of a thematic, keyword\u2010based literature search, we performed an ethical analysis against established frameworks of biomedical ethics. We combined our results with current, relevant normative machine learning ethics literature to identify the status quo of the ethics of ML\u2010HCAs in dermatology. We describe the benefits and risks of dermatological ML\u2010HCAs that are currently being developed for clinical purposes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The potential benefits range from better patient outcomes to better knowledge accessibility to decreasing health care disparities, that is, standards of care between different population groups. The risks associated with ML\u2010HCAs range from confidentiality issues to individual patient outcomes as well as the exacerbation of prevalent health care disparities. We discuss the practical implications for all stages of dermatological ML\u2010HCA development.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>We found that ML\u2010HCAs present stakeholder\u2010specific risks for patients, health care professionals and society, which need to be considered separately. The discipline lacks sufficient biomedical ethics research that could standardize the approach to ML\u2010HCA model design, training, use and regulation of such technologies.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jdv.18192","type":"journal-article","created":{"date-parts":[[2022,5,1]],"date-time":"2022-05-01T12:22:56Z","timestamp":1651407776000},"page":"1660-1668","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Risks and benefits of dermatological machine learning health care applications\u2014an overview and ethical analysis"],"prefix":"10.1111","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7643-8816","authenticated-orcid":false,"given":"T.","family":"Willem","sequence":"first","affiliation":[{"name":"School of Medicine, Institute of History and Ethics in Medicine Technical University of Munich  Munich Germany"},{"name":"Department of Science, Technology and Society (STS), School of Social 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