Generalizability and usefulness of artificial intelligence for skin cancer diagnostics: An algorithm validation study-Reference-Cited by-同舟云学术

Generalizability and usefulness of artificial intelligence for skin cancer diagnostics: An algorithm validation study

Published:2022-10-03 Issue:4 Volume:1 Page:344-354
ISSN:2768-6566
Container-title:JEADV Clinical Practice
language:en
Short-container-title:JEADV Clinical Practice

Author:

Ternov Niels K.¹^ORCID,Christensen Anders N.²,Kampen Peter J. T.²,Als Gustav²,Vestergaard Tine³^ORCID,Konge Lars⁴⁵^ORCID,Tolsgaard Martin⁴⁵,Hölmich Lisbet R.¹⁵,Guitera Pascale⁶⁷,Chakera Annette H.¹⁵,Hannemose Morten R.²

Affiliation:

1. Department of Plastic Surgery Herlev and Gentofte University Hospital Copenhagen Denmark

2. Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

3. Department of Dermatology and Allergy Center Odense University Hospital Odense Denmark

4. Copenhagen Academy for Medical Education and Simulation Copenhagen University Hospital ‐ Rigshospitalet Copenhagen Denmark

5. Department of Clinical Medicine University of Copenhagen Copenhagen Denmark

6. Melanoma Institute Australia Sydney The University of Sydney Sydney New South Wales Australia

7. Sydney Melanoma Diagnostic Centre Royal Prince Alfred Hospital Sydney New South Wales Australia

Funder

Innovationsfonden

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jvc2.59

Reference44 articles.

1. The Growing Burden of Invasive Melanoma: Projections of Incidence Rates and Numbers of New Cases in Six Susceptible Populations through 2031

2. Prevalence and Costs of Skin Cancer Treatment in the U.S., 2002−2006 and 2007−2011

3. Reliable test of clinicians’ mastery in skin cancer diagnostics

4. Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

5. The Performance of MelaFind

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