Your browser doesn't support javascript.
loading
Combining Automated Lesion Risk and Change Assessment Improves Melanoma Detection: A Retrospective Accuracy Study.
Rutjes, Chantal; Mothershaw, Adam; D'Alessandro, Brian M; Primiero, Clare A; McInerney-Leo, Aideen; Soyer, H Peter; Janda, Monika; Betz-Stablein, Brigid.
Afiliação
  • Rutjes C; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia. Electronic address: c.rutjes@uq.edu.au.
  • Mothershaw A; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
  • D'Alessandro BM; Canfield Scientific, Parsippany, New Jersey, USA.
  • Primiero CA; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia.
  • McInerney-Leo A; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia.
  • Soyer HP; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia; Dermatology Department, Princess Alexandra Hospital, Brisbane, Australia.
  • Janda M; Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, Australia.
  • Betz-Stablein B; Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Australia.
J Invest Dermatol ; 2024 Sep 07.
Article em En | MEDLINE | ID: mdl-39182563
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Invest Dermatol Ano de publicação: 2024 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: J Invest Dermatol Ano de publicação: 2024 Tipo de documento: Article