Clinical decision support of radiotherapy treatment planning: A data-driven machine learning strategy for patient-specific dosimetric decision making.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Nov 20, 2017

Abstract

BACKGROUND AND PURPOSE: Clinical decision support systems are a growing class of tools with the potential to impact healthcare. This study investigates the construction of a decision support system through which clinicians can efficiently identify which previously approved historical treatment plans are achievable for a new patient to aid in selection of therapy.

Authors

  • Gilmer Valdes
    Department of Radiation Oncology, University of California, San Francisco, California.
  • Charles B Simone
    Department of Radiation Oncology, University of Maryland Medical Center.
  • Josephine Chen
    Biomedical Informatics Training Program, Stanford University, Stanford, CA.
  • Alexander Lin
    Department of Radiation Oncology, University of Pennsylvania, Philadelphia, United States.
  • Sue S Yom
    Department of Radiation Oncology, University of California, San Francisco, California.
  • Adam J Pattison
    Siris Medical Inc, Burlingame, California.
  • Colin M Carpenter
    Siris Medical, Redwood City, United States.
  • Timothy D Solberg
    U.S. Food and Drug Administration, Silver Spring, Maryland.

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