摘要
放射治疗是癌症的主要治疗手段之一,以机器学习为代表的人工智能飞速发展,可应用于放射治疗临床实践的各个环节,包括临床决策支持、自动勾画靶区、预测疗效和副反应等,提高准确性与效率。尽管面临着结构化数据缺乏、模型可解释性差等挑战,机器学习在放射治疗中的应用将日趋深刻而广泛。本文从机器学习简介、在放射治疗中的临床应用研究进展和挑战与解决之道等3个方面展开综述。
Radiation therapy is one of the main treatment methods for cancer.Machine learning can be used in all aspects of clinical practice in radiation therapy,including clinical decision support,automatic segmentation of target volumes,prediction of treatment efficacy and side effects.Despite the challenges of lacking structured data and poor interpretability of models,the application of machine learning in radiotherapy will become increasingly profound and extensive.This review contains three aspects:introduction of machine learning,the clinical application of machine learning in radiotherapy,challenges and solutions.
作者
马泽良
门阔
蒋海行
惠周光
Ma Zeliang;Men Kuo;Jiang Haihang;Hui Zhouguang(Department of Radiation Oncology,National Cancer Center,National Clinical Research Center for Cancer,Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China;Suzhou Xunzheng Medical Technology Co.,Ltd.Department of Research and Development,Suzhou 215000,China;Department of VIP Medical Services,National Cancer Center,National Clinical Research Center for Cancer,Cancer Hospital,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing 100021,China)
出处
《中华放射医学与防护杂志》
CAS
CSCD
北大核心
2021年第2期155-159,共5页
Chinese Journal of Radiological Medicine and Protection
基金
国家重点研发项目(2017YFC1311000,2017YFC1311002,2018YFC0116800)。
关键词
机器学习
人工智能
放射治疗
Machine learning
Artificial intelligence
Radiation oncology
