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Optimizing risk-based breast cancer screening policies with reinforcement learning.
Yala, Adam; Mikhael, Peter G; Lehman, Constance; Lin, Gigin; Strand, Fredrik; Wan, Yung-Liang; Hughes, Kevin; Satuluru, Siddharth; Kim, Thomas; Banerjee, Imon; Gichoya, Judy; Trivedi, Hari; Barzilay, Regina.
Afiliación
  • Yala A; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. adamyala@csail.mit.edu.
  • Mikhael PG; Jameel Clinic, Massachusetts Institute of Technology, Cambridge, MA, USA. adamyala@csail.mit.edu.
  • Lehman C; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Lin G; Jameel Clinic, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Strand F; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Wan YL; Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
  • Hughes K; Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City, Taiwan.
  • Satuluru S; Breast Radiology Unit, Department of Imaging and Physiology, Karolinska University Hospital, Solna, Sweden.
  • Kim T; Department of Oncology-Pathology, Karolinska Institute, Solna, Sweden.
  • Banerjee I; Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
  • Gichoya J; Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan City, Taiwan.
  • Trivedi H; Department of Surgery, Medical University of South Carolina, Charleston, SC, USA.
  • Barzilay R; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA.
Nat Med ; 28(1): 136-143, 2022 01.
Article en En | MEDLINE | ID: mdl-35027757
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inteligencia Artificial / Mamografía Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Female / Humans Idioma: En Revista: Nat Med Asunto de la revista: BIOLOGIA MOLECULAR / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Inteligencia Artificial / Mamografía Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Female / Humans Idioma: En Revista: Nat Med Asunto de la revista: BIOLOGIA MOLECULAR / MEDICINA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos