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Machine Learning and Radiogenomics: Lessons Learned and Future Directions.
Kang, John; Rancati, Tiziana; Lee, Sangkyu; Oh, Jung Hun; Kerns, Sarah L; Scott, Jacob G; Schwartz, Russell; Kim, Seyoung; Rosenstein, Barry S.
Afiliação
  • Kang J; Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY, United States.
  • Rancati T; Prostate Cancer Program, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
  • Lee S; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
  • Oh JH; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States.
  • Kerns SL; Department of Radiation Oncology, University of Rochester Medical Center, Rochester, NY, United States.
  • Scott JG; Department of Translational Hematology and Oncology Research, Cleveland Clinic, Cleveland, OH, United States.
  • Schwartz R; Department of Radiation Oncology, Cleveland Clinic, Cleveland, OH, United States.
  • Kim S; Computational Biology Department, Carnegie Mellon School of Computer Science, Pittsburgh, PA, United States.
  • Rosenstein BS; Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, United States.
Front Oncol ; 8: 228, 2018.
Article em En | MEDLINE | ID: mdl-29977864
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Patient_preference Idioma: En Revista: Front Oncol Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Patient_preference Idioma: En Revista: Front Oncol Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça