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1 Ergebnisse
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Determining the clinical applicability of machine learning ..:
Steele, Lloyd
;
Tan, Xiang Li
;
Olabi, Bayanne
...
Journal of the European Academy of Dermatology and Venereology. 37 (2023) 4 - p. 657-665 , 2023
Link:
https://doi.org/10.1111/jdv.18814
RT Journal T1 <Title>Determining the clinical applicability of machine learning models through assessment of reporting across skin phototypes and rarer skin cancer types: A systematic review</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1111_jdv.18814&Exemplar=1&LAN=DE A1 Steele, Lloyd A1 Tan, Xiang Li A1 Olabi, Bayanne A1 Gao, Jing Mia A1 Tanaka, Reiko J. A1 Williams, Hywel C. PB Wiley YR 2023 SN 0926-9959 SN 1468-3083 JF Journal of the European Academy of Dermatology and Venereology VO 37 IS 4 SP 657 OP 665 LK http://dx.doi.org/https://doi.org/10.1111/jdv.18814 DO https://doi.org/10.1111/jdv.18814 SF ELIB - SuUB Bremen
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