To explore the predictive performance of machine learning on the recurrence of patients with gastric cancer after the operation. The available data is divided into two parts. In particular, the first part is used as a training set (such as 80% of the original data), and the second part is used as a test set (the remaining 20% of the data). And we use fivefold cross-validation. The weight of recurrence factors shows the top four factors are BMI, Operation time, WGT and age in order. In training group:among the 5 machine learning models, the accuracy of gbm was 0.891, followed by gbm algorithm was 0.876; The AUC values of the five machine learning algorithms are from high to low as forest (0.962), gbm (0.922), GradientBoosting (0.898), DecisionTree (0.790) and Logistic (0.748). And the precision of the forest is the highest 0.957, followed by the GradientBoosting algorithm (0.878). At the same time, in the test group is as follows: the highest accuracy of Logistic was 0.801, followed by forest algorithm and gbm; the AUC values of the five algorithms are forest (0.795), GradientBoosting (0.774), DecisionTree (0.773), Logistic (0.771) and gbm (0.771), from high to low. Among the five machine learning algorithms, the highest precision rate of Logistic is 1.000, followed by the gbm (0.487). Machine learning can predict the recurrence of gastric cancer patients after an operation. Besides, the first four factors affecting postoperative recurrence of gastric cancer were BMI, Operation time, WGT and age.

探讨机器学习对胃癌患者术后复发的预测性能。可用数据分为两部分。特别地，第一部分用作训练集（如原始数据的80%），第二部分用作测试集（其余20%的数据）。我们使用五重交叉验证。复发因素的权重显示，排名前四的因素依次为BMI、手术时间、WGT和年龄。训练组：5个机器学习模型中，gbm的准确率为0.891，gbm算法次之，为0.876；五种机器学习算法的AUC值从高到低依次为forest（0.962）、gbm（0.922）、GradientBoosting（0.898）、DecisionTree（0.790）和Logistic（0.748）。而森林的精度最高的是0.957，其次是 GradientBoosting 算法 (0.878)。同时，在测试组中如下：Logistic的最高准确率为0.801，其次是forest algorithm和gbm；五种算法的AUC值从高到低依次为forest（0.795）、GradientBoosting（0.774）、DecisionTree（0.773）、Logistic（0.771）和gbm（0.771）。在五种机器学习算法中，Logistic 的最高准确率是 1.000，其次是 gbm（0.487）。机器学习可以预测胃癌患者手术后的复发情况。此外，影响胃癌术后复发的前4个因素是BMI、手术时间、WGT和年龄。五种算法的AUC值从高到低依次为forest（0.795）、GradientBoosting（0.774）、DecisionTree（0.773）、Logistic（0.771）和gbm（0.771）。在五种机器学习算法中，Logistic 的最高准确率是 1.000，其次是 gbm（0.487）。机器学习可以预测胃癌患者手术后的复发情况。此外，影响胃癌术后复发的前4个因素是BMI、手术时间、WGT和年龄。五种算法的AUC值从高到低依次为forest（0.795）、GradientBoosting（0.774）、DecisionTree（0.773）、Logistic（0.771）和gbm（0.771）。在五种机器学习算法中，Logistic 的最高准确率是 1.000，其次是 gbm（0.487）。机器学习可以预测胃癌患者手术后的复发情况。此外，影响胃癌术后复发的前4个因素是BMI、手术时间、WGT和年龄。