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External Validation of an Ensemble Model for Automated Mammography Interpretation by Artificial Intelligence.
Hsu, William; Hippe, Daniel S; Nakhaei, Noor; Wang, Pin-Chieh; Zhu, Bing; Siu, Nathan; Ahsen, Mehmet Eren; Lotter, William; Sorensen, A Gregory; Naeim, Arash; Buist, Diana S M; Schaffter, Thomas; Guinney, Justin; Elmore, Joann G; Lee, Christoph I.
Afiliação
  • Hsu W; Medical and Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine at University California, Los Angeles.
  • Hippe DS; Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, Washington.
  • Nakhaei N; Medical and Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine at University California, Los Angeles.
  • Wang PC; Department of Medicine, David Geffen School of Medicine at University California, Los Angeles.
  • Zhu B; Medical and Imaging Informatics, Department of Radiological Sciences, David Geffen School of Medicine at University California, Los Angeles.
  • Siu N; Medical Informatics Home Area, Graduate Programs in Biosciences, David Geffen School of Medicine at University California, Los Angeles, Los Angeles, California.
  • Ahsen ME; Gies College of Business, University of Illinois at Urbana-Champaign.
  • Lotter W; DeepHealth, RadNet AI Solutions, Cambridge, Massachusetts.
  • Sorensen AG; DeepHealth, RadNet AI Solutions, Cambridge, Massachusetts.
  • Naeim A; Center for Systematic, Measurable, Actionable, Resilient, and Technology-driven Health, Clinical and Translational Science Institute, David Geffen School of Medicine at University California, Los Angeles.
  • Buist DSM; Kaiser Permanente Washington Health Research Institute, Seattle, Washington.
  • Schaffter T; Computational Oncology, Sage Bionetworks, Seattle, Washington.
  • Guinney J; Tempus Labs, Chicago, Illinois.
  • Elmore JG; Department of Medicine, David Geffen School of Medicine at University California, Los Angeles.
  • Lee CI; Department of Radiology, University of Washington School of Medicine, Seattle.
JAMA Netw Open ; 5(11): e2242343, 2022 11 01.
Article em En | MEDLINE | ID: mdl-36409497
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Mamografia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Adult / Female / Humans / Middle aged Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Mamografia Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Adult / Female / Humans / Middle aged Idioma: En Ano de publicação: 2022 Tipo de documento: Article