Commentary: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance

Alexander D G Anderson; Serigne N Lo; Pascale Guitera

doi:10.3389/fmed.2024.1345659

Commentary: Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance

Front Med (Lausanne). 2024 Feb 6:11:1345659. doi: 10.3389/fmed.2024.1345659. eCollection 2024.

Authors

Alexander D G Anderson^{1

2}, Serigne N Lo^{3

4}, Pascale Guitera^{3

4

5}

Affiliations

¹ Royal Cornwall Hospital Trust, Truro, United Kingdom.
² University of Exeter, Exeter, United Kingdom.
³ Melanoma Institute Australia, Sydney, NSW, Australia.
⁴ The University of Sydney, Darlington, NSW, Australia.
⁵ Sydney Melanoma Diagnostic Centre (SMDC), Camperdown, NSW, Australia.

No abstract available

Keywords: AI as a medical device; AI for skin cancer; DERM; Skin Analytics; artificial intelligence; deep ensemble for the recognition of malignancy; skin cancer.

Publication types

Comment

Grants and funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.