Literature DB >> 30714102

Can clinical decision making be enhanced by artificial intelligence?

M Janda1, H P Soyer2,3.   

Abstract

Mesh：

Year:  2019        PMID： 30714102     DOI： 10.1111/bjd.17110

Source DB:  PubMed          Journal:  Br J Dermatol        ISSN： 0007-0963            Impact factor:   9.302


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  4 in total

Review 1.  Machine learning for precision dermatology: Advances, opportunities, and outlook.

Authors:  Ernest Y Lee; Nolan J Maloney; Kyle Cheng; Daniel Q Bach
Journal:  J Am Acad Dermatol       Date:  2020-07-06       Impact factor: 11.527

Review 2.  The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.

Authors:  Claire M Felmingham; Nikki R Adler; Zongyuan Ge; Rachael L Morton; Monika Janda; Victoria J Mar
Journal:  Am J Clin Dermatol       Date:  2021-03       Impact factor: 7.403

3.  A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology.

Authors:  Jane Scheetz; Philip Rothschild; Myra McGuinness; Xavier Hadoux; H Peter Soyer; Monika Janda; James J J Condon; Luke Oakden-Rayner; Lyle J Palmer; Stuart Keel; Peter van Wijngaarden
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

4.  Evaluation of the Diagnostic Accuracy of an Online Artificial Intelligence Application for Skin Disease Diagnosis.

Authors:  Oscar Zaar; Alexander Larson; Sam Polesie; Karim Saleh; Mikael Tarstedt; Antonio Olives; Andrea Suárez; Martin Gillstedt; Noora Neittaanmäki
Journal:  Acta Derm Venereol       Date:  2020-09-16       Impact factor: 3.875
  4 in total

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