Your browser doesn't support javascript.
loading
Using Big Data Analytics to Advance Precision Radiation Oncology.
McNutt, Todd R; Benedict, Stanley H; Low, Daniel A; Moore, Kevin; Shpitser, Ilya; Jiang, Wei; Lakshminarayanan, Pranav; Cheng, Zhi; Han, Peijin; Hui, Xuan; Nakatsugawa, Minoru; Lee, Junghoon; Moore, Joseph A; Robertson, Scott P; Shah, Veeraj; Taylor, Russ; Quon, Harry; Wong, John; DeWeese, Theodore.
Afiliación
  • McNutt TR; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland. Electronic address: tmcnutt1@jhmi.edu.
  • Benedict SH; Department of Radiation Oncology, University of California, Davis, Sacramento, California.
  • Low DA; Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California.
  • Moore K; Radiation Medicine and Applied Sciences, University of California, San Diego, La Jolla, California.
  • Shpitser I; Department of Computer Science, Johns Hopkins University, Baltimore, Maryland.
  • Jiang W; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Lakshminarayanan P; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Cheng Z; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Han P; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Hui X; Department of Public Health Sciences, University of Chicago, Chicago, Illinois.
  • Nakatsugawa M; Canon Medical Systems Corporation.
  • Lee J; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Moore JA; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Robertson SP; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Shah V; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Taylor R; Department of Computer Science, Johns Hopkins University, Baltimore, Maryland.
  • Quon H; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • Wong J; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
  • DeWeese T; Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, Maryland.
Int J Radiat Oncol Biol Phys ; 101(2): 285-291, 2018 06 01.
Article en En | MEDLINE | ID: mdl-29726357
Asunto(s)
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Oncología por Radiación / Sistemas de Apoyo a Decisiones Clínicas / Medicina de Precisión / Aprendizaje Automático / Macrodatos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Radiat Oncol Biol Phys Año: 2018 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Oncología por Radiación / Sistemas de Apoyo a Decisiones Clínicas / Medicina de Precisión / Aprendizaje Automático / Macrodatos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Radiat Oncol Biol Phys Año: 2018 Tipo del documento: Article