基于机器学习的口咽癌死亡预测模型构建与研究

Construction and Research on Oropharyngeal Cancer Death Prediction Model Based on Machine Learning

采用机器学习对口咽癌患者一年生存情况构建预测模型,通过比较找到最优模型,以期为相关疾病预后提供可靠的参考指标。选取SEER数据库中2020年的口咽癌患者2 636例,数据经过SMOTE算法优化后,运用八种机器学习方法建立预测分类模型比较分析。基于随机森林、决策树算法的模型相对来说预测性能更佳。机器学习算法建立的预测模型能够较好地辅助口咽癌临床诊疗及预后相关行为。

Machine Learning is used to construct a prediction model for the annual survival situation of oropharyngeal cancer patients.In order to provide a reliable reference index for the prognosis of related diseases,the optimal model is found through comparison.And 2636 patients with oropharyngeal cancer in 2020 from the SEER database are selected.After the data are optimized by SMOTE algorithm,eight Machine Learning methods are used to establish a predictive classification model for comparative analysis.The Models based on Random Forest and Decision Tree algorithm have better predictive performance,relatively.The prediction model established by the Machine Learning algorithm can effectively assist the clinical diagnosis and treatment of oropharyngeal cancer and prognostic behaviors.