Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD.
Department of Radiation Medicine and Applied Sciences, University of California - San Diego, La Jolla, CA.
Semin Radiat Oncol. 2019 Oct;29(4):326-332. doi: 10.1016/j.semradonc.2019.05.006.
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.
大数据在放射治疗质量保证中的应用是多方面的。大数据可以通过统计手段以及更先进的机器学习和人工智能来检测异常和次优的质量指标。通过对指南依从性、轮廓完整性、治疗传递机制和治疗计划质量的例子来讨论这些方法在临床实践中的应用。最终目标是将大数据方法应用于直接衡量患者护理质量的结果。大数据和机器学习的时代正在成熟,质量保证的实施有望提高患者的护理质量。