Construction and Research on Oropharyngeal Cancer Death Prediction Model Based on Machine Learning
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 2 636 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.
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