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Real-world post-deployment performance of a novel machine l..:
Lucy Thomas
;
Chris Hyde
;
Dan Mullarkey
...
https://www.frontiersin.org/articles/10.3389/fmed.2023.1264846/full. , 2023
Link:
https://doi.org/10.3389/fmed.2023.1264846
RT Journal T1 <Title>Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:2bcdfdadf6204b8492c58238de681f1d&Exemplar=1&LAN=DE A1 Lucy Thomas A1 Chris Hyde A1 Dan Mullarkey A1 Jack Greenhalgh A1 Dilraj Kalsi A1 Justin Ko PB Frontiers Media S.A. YR 2023 K1 artificial intelligence K1 skin cancer K1 AI for skin cancer K1 AI as a medical device K1 DERM K1 deep ensemble for the recognition of malignancy K1 Medicine (General) K1 R5-920 JF https://www.frontiersin.org/articles/10.3389/fmed.2023.1264846/full LK http://dx.doi.org/https://doi.org/10.3389/fmed.2023.1264846 DO https://doi.org/10.3389/fmed.2023.1264846 SF ELIB - SuUB Bremen
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