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Recommendations for the development and use of imaging test sets to investigate the test performance of artificial intelligence in health screening.
Chalkidou, Anastasia; Shokraneh, Farhad; Kijauskaite, Goda; Taylor-Phillips, Sian; Halligan, Steve; Wilkinson, Louise; Glocker, Ben; Garrett, Peter; Denniston, Alastair K; Mackie, Anne; Seedat, Farah.
Afiliação
  • Chalkidou A; King's Technology Evaluation Centre, King's College London, London, UK. Electronic address: anastasia.chalkidou@nice.org.uk.
  • Shokraneh F; King's Technology Evaluation Centre, King's College London, London, UK.
  • Kijauskaite G; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
  • Taylor-Phillips S; Warwick Medical School, University of Warwick, Coventry, UK.
  • Halligan S; Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
  • Wilkinson L; Oxford Breast Imaging Centre, Oxford University, Oxford, UK.
  • Glocker B; Department of Computing, Imperial College London, London, UK.
  • Garrett P; Department of Chemical Engineering and Analytical Science, University of Manchester, Manchester, UK.
  • Denniston AK; Department of Ophthalmology, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK.
  • Mackie A; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
  • Seedat F; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
Lancet Digit Health ; 4(12): e899-e905, 2022 12.
Article em En | MEDLINE | ID: mdl-36427951
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Diagnóstico por Imagem Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Revista: Lancet Digit Health Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Diagnóstico por Imagem Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Revista: Lancet Digit Health Ano de publicação: 2022 Tipo de documento: Article