利用逻辑回归模型预测宫颈癌的致病因素

Using Logistic Regression Model to Predict the Pathogenic Factors of Cervical Cancer

妇科中的第二位恶性肿瘤是宫颈癌,它能够导致女性癌症相关死亡,最近的一份报告预测2021年新发宫颈癌患者14480例,其中4290人将死亡。文章利用逻辑回归方法在python环境下根据收集到的一些致病因素建立宫颈癌预测模型,将原始数据集分为两部分,分别是训练集和测试集,其中根据训练集来建立预测模型,再将测试集应用在模型上对模型进行验证,计算出其准确率为80%。本文结果表明,该模型在预测宫颈癌风险的应用上具有一定价值。

The second malignant tumor in gynecology is cervical cancer, which can lead to cancer-related deaths in women.A recent report predicts 14480 new cervical cancer patients in 2021, of which 4290 will die. In this paper, the logistic regression method is used to establish the prediction model of cervical cancer according to some collected pathogenic factors in Python environment. The original data set is divided into two parts: training set and test set. The prediction model is established according to the training set, and then the test set is applied to the model to verify the model. The accuracy is calculated to be 80%. The results show that the model has certain value in predicting the risk of cervical cancer.