鼻咽癌放疗后大出血风险机器学习预测模型构建

Construction of a Machine Learning Prediction Model for the Risk of Massive Hemorrhage After Radiotherapy for Nasopharyngeal Carcinoma

目的/意义构建鼻咽癌放疗后大出血风险预测模型,并评价其预测效能。方法/过程选取郑州大学第一附属医院2016—2019年鼻咽癌放疗后大出血的住院患者为研究对象,随机选取同等数量未出现大出血的患者为对照组,收集两组患者的病历指标数据,分别应用多种机器学习算法并选取最优算法构建模型。结果/结论基于支持向量机算法的模型召回率为0.94、F 1值为0.93、精确度为0.93,效果最好,可用于构建鼻咽癌放疗后大出血预测模型,为患者提供更精确的个体化预测,具有良好的临床应用前景。

Purpose/Significance To construct a risk prediction model for postoperative massive bleeding in nasopharyngeal carcinoma after radiotherapy,and to evaluate its predictive performance.Method/Process Inpatients with major bleeding after radiotherapy for nasopharyngeal cancer in the First Affiliated Hospital of Zhengzhou University from 2016 to 2019 are selected as the study objects,and the same number of patients without major bleeding are randomly selected as the control group.The medical record index data of the two groups of patients are collected,and various machine learning algorithms are applied respectively and the optimal algorithm is selected to build the model.Result/Conclusion The model based on support vector machine(SVM)algorithm has a recall rate of 0.94,an F 1 value of 0.93,and a precision of 0.93,showing the best performance.It can be used to construct a prediction model for postoperative massive bleeding in nasopharyngeal carcinoma,and provide more accurate personalized prediction for patients,which has good clinical application prospects.