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Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time.
Matthew, Jacqueline; Skelton, Emily; Day, Thomas G; Zimmer, Veronika A; Gomez, Alberto; Wheeler, Gavin; Toussaint, Nicolas; Liu, Tianrui; Budd, Samuel; Lloyd, Karen; Wright, Robert; Deng, Shujie; Ghavami, Nooshin; Sinclair, Matthew; Meng, Qingjie; Kainz, Bernhard; Schnabel, Julia A; Rueckert, Daniel; Razavi, Reza; Simpson, John; Hajnal, Jo.
Afiliação
  • Matthew J; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Skelton E; Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Day TG; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Zimmer VA; Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Gomez A; School of Health Sciences, City University of London, London, UK.
  • Wheeler G; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Toussaint N; Guy's and St Thomas' NHS Foundation Trust, London, UK.
  • Liu T; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Budd S; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Lloyd K; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Wright R; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Deng S; Department of Computing, Imperial College London, London, UK.
  • Ghavami N; Department of Computing, Imperial College London, London, UK.
  • Sinclair M; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Meng Q; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Kainz B; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Schnabel JA; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Rueckert D; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
  • Razavi R; Department of Computing, Imperial College London, London, UK.
  • Simpson J; Department of Computing, Imperial College London, London, UK.
  • Hajnal J; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Prenat Diagn ; 42(1): 49-59, 2022 Jan.
Article em En | MEDLINE | ID: mdl-34648206
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Inteligência Artificial / Ultrassonografia Pré-Natal Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies Limite: Adult / Female / Humans / Pregnancy Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Anormalidades Congênitas / Inteligência Artificial / Ultrassonografia Pré-Natal Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies Limite: Adult / Female / Humans / Pregnancy Idioma: En Ano de publicação: 2022 Tipo de documento: Article