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The current and future roles of artificial intelligence in pediatric radiology.
Otjen, Jeffrey P; Moore, Michael M; Romberg, Erin K; Perez, Francisco A; Iyer, Ramesh S.
Afiliação
  • Otjen JP; Department of Radiology, Seattle Children's Hospital, University of Washington School of Medicine, 4800 Sand Point Way NE, MA.7.220, Seattle, WA, 98105, USA.
  • Moore MM; Department of Radiology, Penn State Children's Hospital, Penn State Health System, Hershey, PA, USA.
  • Romberg EK; Department of Radiology, Seattle Children's Hospital, University of Washington School of Medicine, 4800 Sand Point Way NE, MA.7.220, Seattle, WA, 98105, USA.
  • Perez FA; Department of Radiology, Seattle Children's Hospital, University of Washington School of Medicine, 4800 Sand Point Way NE, MA.7.220, Seattle, WA, 98105, USA.
  • Iyer RS; Department of Radiology, Seattle Children's Hospital, University of Washington School of Medicine, 4800 Sand Point Way NE, MA.7.220, Seattle, WA, 98105, USA. riyer@uw.edu.
Pediatr Radiol ; 52(11): 2065-2073, 2022 10.
Article em En | MEDLINE | ID: mdl-34046708
ABSTRACT
Artificial intelligence (AI) is a broad and complicated concept that has begun to affect many areas of medicine, perhaps none so much as radiology. While pediatric radiology has been less affected than other radiology subspecialties, there are some well-developed and some nascent applications within the field. This review focuses on the use of AI within pediatric radiology for image interpretation, with descriptive summaries of the literature to date. We highlight common features that enable successful application of the technology, along with some of the limitations that can inhibit the development of this field. We present some ideas for further research in this area and challenges that must be overcome, with an understanding that technology often advances in unpredictable ways.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiologia / Inteligência Artificial Tipo de estudo: Prognostic_studies Limite: Child / Humans Idioma: En Revista: Pediatr Radiol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiologia / Inteligência Artificial Tipo de estudo: Prognostic_studies Limite: Child / Humans Idioma: En Revista: Pediatr Radiol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos