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A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction.
Yala, Adam; Lehman, Constance; Schuster, Tal; Portnoi, Tally; Barzilay, Regina.
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  • Yala A; From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32 Vassar St, 32-G484, Cambridge, MA 02139 (A.Y., T.S., T.P., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.L.).
  • Lehman C; From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32 Vassar St, 32-G484, Cambridge, MA 02139 (A.Y., T.S., T.P., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.L.).
  • Schuster T; From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32 Vassar St, 32-G484, Cambridge, MA 02139 (A.Y., T.S., T.P., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.L.).
  • Portnoi T; From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32 Vassar St, 32-G484, Cambridge, MA 02139 (A.Y., T.S., T.P., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.L.).
  • Barzilay R; From the Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 32 Vassar St, 32-G484, Cambridge, MA 02139 (A.Y., T.S., T.P., R.B.); and Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Mass (C.L.).
Radiology ; 292(1): 60-66, 2019 07.
Article en En | MEDLINE | ID: mdl-31063083
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Mamografía / Interpretación de Imagen Radiográfica Asistida por Computador / Aprendizaje Profundo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Radiology Año: 2019 Tipo del documento: Article
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Mamografía / Interpretación de Imagen Radiográfica Asistida por Computador / Aprendizaje Profundo Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Middle aged Idioma: En Revista: Radiology Año: 2019 Tipo del documento: Article