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Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis.
Kobayashi, Soma; Shieh, Jason; Ruiz de Sabando, Ainara; Kim, Julie; Liu, Yang; Zee, Sui Y; Prasanna, Prateek; Bialkowska, Agnieszka B; Saltz, Joel H; Yang, Vincent W.
Afiliación
  • Kobayashi S; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States of America.
  • Shieh J; Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
  • Ruiz de Sabando A; Department of Medical Genetics, Complejo Hospitalario de Navarra, Pamplona, Navarra, Spain.
  • Kim J; Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
  • Liu Y; Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
  • Zee SY; Department of Pathology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
  • Prasanna P; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States of America.
  • Bialkowska AB; Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
  • Saltz JH; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States of America.
  • Yang VW; Department of Pathology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, United States of America.
PLoS One ; 17(8): e0268954, 2022.
Article en En | MEDLINE | ID: mdl-36037173
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Colitis / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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XML
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Colitis / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos