Use of Big Data for Quality Assurance in Radiation Therapy

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The application of big data to the quality assurance of radiation therapy is multifaceted. Big data can be used to detect anomalies and suboptimal quality metrics through both statistical means and more advanced machine learning and artificial intelligence. The application of these methods to clinical practice is discussed through examples of guideline adherence, contour integrity, treatment delivery mechanics, and treatment plan quality. The ultimate goal is to apply big data methods to direct measures of patient outcomes for care quality. The era of big data and machine learning is maturing and the implementation for quality assurance promises to improve the quality of care for patients.

Original languageEnglish (US)
Pages (from-to)326-332
Number of pages7
JournalSeminars in Radiation Oncology
Volume29
Issue number4
DOIs
StatePublished - Oct 2019

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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