Your browser doesn't support javascript.
loading
Can AI distinguish a bone radiograph from photos of flowers or cars? Evaluation of bone age deep learning model on inappropriate data inputs.
Yi, Paul H; Arun, Anirudh; Hafezi-Nejad, Nima; Choy, Garry; Sair, Haris I; Hui, Ferdinand K; Fritz, Jan.
Afiliación
  • Yi PH; University of Maryland Intelligent Imaging (UMII) Center, Department of Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
  • Arun A; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Hafezi-Nejad N; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Choy G; Department of Radiology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA.
  • Sair HI; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Hui FK; The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Fritz J; Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA. jan.fritz@nyulangone.org.
Skeletal Radiol ; 51(2): 401-406, 2022 Feb.
Article en En | MEDLINE | ID: mdl-34351456
Asunto(s)
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies Límite: Child / Humans Idioma: En Revista: Skeletal Radiol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies Límite: Child / Humans Idioma: En Revista: Skeletal Radiol Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos