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Title:

Risks and benefits of dermatological machine learning health care applications-an overview and ethical analysis.

Document type:
Journal Article
Author(s):
Willem, T; Krammer, S; Böhm, A-S; French, L E; Hartmann, D; Lasser, T; Buyx, A
Abstract:
BACKGROUND: 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-HCAs). To date, several ML-HCAs have detected malignant skin lesions on par with experts or found overlooked visual patterns that correlate with certain dermatological diseases....     »
Journal title abbreviation:
J Eur Acad Dermatol Venereol
Year:
2022
Journal volume:
36
Journal issue:
9
Pages contribution:
1660-1668
Fulltext / DOI:
doi:10.1111/jdv.18192
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/35490413
Print-ISSN:
0926-9959
TUM Institution:
Institut für Geschichte und Ethik der Medizin
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