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Artificial intelligence in dermatology for the clinician.
Patel, Shaan; Wang, Jordan V; Motaparthi, Kiran; Lee, Jason B.
Afiliação
  • Patel S; Department of Dermatology, Temple University Lewis Katz School of Medicine, Philadelphia, Pennsylvania, USA.
  • Wang JV; Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, USA.
  • Motaparthi K; Department of Dermatology, University of Florida College of Medicine, Gainesville, Florida, USA.
  • Lee JB; Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania, USA. Electronic address: jason.lee@jefferson.edu.
Clin Dermatol ; 39(4): 667-672, 2021.
Article em En | MEDLINE | ID: mdl-34809771
ABSTRACT
As medicine enters the era of artificial intelligence (AI)-augmented practice, dermatology is beginning to witness the integration of AI into the daily practice, particularly in the areas of diagnosis, prognosis, and treatment of skin diseases. Many of the current electronic medical records that dermatologists have incorporated provide guidance in billing, a form of AI at work. The recent advances in visual recognition AI make application and integration of the technology particularly suited for perceptual specialties such as radiology and dermatology. In dermatology, AI is poised to improve the efficiency and accuracy of traditional diagnostic approaches, including visual examination, skin biopsy, and histopathologic examination. This review highlights the current progress of AI in dermatology and provides a basic overview of the technology.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dermatopatias / Dermatologia Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Dermatopatias / Dermatologia Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article