Literature DB >> 30140854

How Should Artificial Intelligence Screen for Skin Cancer and Deliver Diagnostic Predictions to Patients?

George A Zakhem1, Catherine C Motosko1, Roger S Ho1.   

Abstract

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Year:  2018        PMID： 30140854     DOI： 10.1001/jamadermatol.2018.2714

Source DB:  PubMed          Journal:  JAMA Dermatol        ISSN： 2168-6068            Impact factor:   10.282


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  4 in total

1.  Artificial intelligence and diagnosis in general practice.

Authors:  Nick Summerton; Martin Cansdale
Journal:  Br J Gen Pract       Date:  2019-07       Impact factor: 5.386

2.  Embracing machine learning and digital health technology for precision dermatology.

Authors:  Shannon Wongvibulsin; Byron Kalm-Tsun Ho; Shawn G Kwatra
Journal:  J Dermatolog Treat       Date:  2019-06-14       Impact factor: 3.359

3.  The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population.

Authors:  Mark Lee Willingham; Shane Y P K Spencer; Christopher A Lum; Janira M Navarro Sanchez; Terrilea Burnett; John Shepherd; Kevin Cassel
Journal:  Melanoma Res       Date:  2021-12-01       Impact factor: 3.599

4.  Let's address burnout in oncologists and reimagine the way we work.

Authors:  Krithika Murali; Susana Banerjee
Journal:  Nat Rev Clin Oncol       Date:  2019-01       Impact factor: 66.675
  4 in total

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