Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance.

Kerschke, Laura; Weigel, Stefanie; Rodriguez-Ruiz, Alejandro; Karssemeijer, Nico; Heindel, Walter

Kerschke, Laura; Weigel, Stefanie; Rodriguez-Ruiz, Alejandro; Karssemeijer, Nico; Heindel, Walter.

Afiliação

Kerschke L; Institute of Biostatistics and Clinical Research, IBKF, University of Muenster, Schmeddingstrasse 56, 48149, Muenster, Germany. laura.kerschke@ukmuenster.de.
Weigel S; Clinic for Radiology and Reference Center for Mammography Muenster, University of Muenster and University Hospital Muenster, Albert-Schweitzer-Campus 1, 48149, Muenster, Germany.
Rodriguez-Ruiz A; ScreenPoint Medical BV, Toernooiveld 300, 6525, EC, Nijmegen, The Netherlands.
Karssemeijer N; ScreenPoint Medical BV, Toernooiveld 300, 6525, EC, Nijmegen, The Netherlands.
Heindel W; Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525, Nijmegen, GA, The Netherlands.

Eur Radiol ; 32(2): 842-852, 2022 Feb.

Article em En | MEDLINE | ID: mdl-34383147

Assuntos

Neoplasias da Mama; Aprendizado Profundo; Inteligência Artificial; Neoplasias da Mama/diagnóstico por imagem; Detecção Precoce de Câncer; Feminino; Humanos; Mamografia; Programas de Rastreamento; Negociação; Estudos Retrospectivos

Palavras-chave

Artificial intelligence; Breast cancer; Mammography; Screening

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Female / Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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