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Smartphone apps for skin cancer diagnosis: Implications for patients and practitioners.
Abbott, Lisa M; Smith, Saxon D.
Afiliação
  • Abbott LM; University of Sydney, Sydney Law School, Sydney, New South Wales, Australia.
  • Smith SD; Skin and Cancer Foundation Australia, Sydney, New South Wales, Australia.
Australas J Dermatol ; 59(3): 168-170, 2018 Aug.
Article em En | MEDLINE | ID: mdl-29292506
A research team at Stanford recently reported that their deep convolutional neural network had learned to classify skin cancer with a level of competence equivalent to that of board-certified dermatologists. It is possible that in time, and using larger datasets, such software may surpass the average doctor in diagnostic ability, and that highly accurate technology may be available to both clinicians and patients via smartphones. This technology is poised to change the landscape of skin cancer diagnosis for both physicians and patients, but whether such changes are beneficial will depend on how they are regulated and implemented.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Papel do Médico / Neoplasias Cutâneas / Interpretação de Imagem Assistida por Computador / Dermatologia / Aplicativos Móveis Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Australas J Dermatol Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Papel do Médico / Neoplasias Cutâneas / Interpretação de Imagem Assistida por Computador / Dermatologia / Aplicativos Móveis Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Australas J Dermatol Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Austrália