Literature DB >> 33581189

Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists.

Titus J Brinker1, Max Schmitt2, Eva I Krieghoff-Henning2, Raymond Barnhill3, Helmut Beltraminelli4, Stephan A Braun5, Richard Carr6, Maria-Teresa Fernandez-Figueras7, Gerardo Ferrara8, Sylvie Fraitag9, Raffaele Gianotti10, Mar Llamas-Velasco11, Cornelia S L Müller12, Antonio Perasole13, Luis Requena14, Omar P Sangueza15, Carlos Santonja16, Hans Starz17, Esmeralda Vale18, Wolfgang Weyers19, Achim Hekler2, Jakob N Kather20, Stefan Fröhling21, Dieter Krahl22, Tim Holland-Letz23, Jochen S Utikal24, Andrea Saggini25, Heinz Kutzner25.   

Abstract

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Year:  2021        PMID： 33581189     DOI： 10.1016/j.jaad.2021.02.009

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN： 0190-9622            Impact factor:   11.527


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  4 in total

1.  Development of an Image Analysis-Based Prognosis Score Using Google's Teachable Machine in Melanoma.

Authors:  Stephan Forchhammer; Amar Abu-Ghazaleh; Gisela Metzler; Claus Garbe; Thomas Eigentler
Journal:  Cancers (Basel)       Date:  2022-04-29       Impact factor: 6.575

2.  Covid, AI, and Robotics-A Neurologist's Perspective.

Authors:  Syed Nizamuddin Ahmed
Journal:  Front Robot AI       Date:  2021-03-25

3.  Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Authors:  Xinrong Lu; Y A Firoozeh Abolhasani Zadeh
Journal:  J Healthc Eng       Date:  2022-03-22       Impact factor: 2.682

Review 4.  Machine Learning and Its Application in Skin Cancer.

Authors:  Kinnor Das; Clay J Cockerell; Anant Patil; Paweł Pietkiewicz; Mario Giulini; Stephan Grabbe; Mohamad Goldust
Journal:  Int J Environ Res Public Health       Date:  2021-12-20       Impact factor: 3.390
  4 in total

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