Application of machine learningin predicting the outcomes and complications of radiotherapy

VernacularTitle:机器学习在预测放疗疗效及并发症中的应用
Author: Shuming ZHANG ¹ ; Jiaqi LI ; Hao WANG ; Rongtao JIANG ; Jing SUI ; Chengyu SHI ; Ruijie YANG
Author Information

1. 100191,北京大学第三医院肿瘤放疗科
Keywords: Machine learning; Radiotherapy; Prognosis; Complication
From: Chinese Journal of Radiological Medicine and Protection 2018;38(10):792-795
CountryChina
Language:Chinese
Abstract: Machine learning has developed rapidly in recent years.Using machine learning to predict the radiotherapy outcomes and complications can more accurately evaluate the patients' conditions and take appropriate treatment measures as soon as possible.The non-dose and dose related factors generated during radiotherapy are filtered and input into the algorithm model,then corresponding prediction result can be obtained.There are many algorithm models to predict survival rate,tumor control rate and radiotherapy complications,and the predicted result are more accurate now.However,the algorithm model also has various problems,and it needs constant exploration and improvement.