Objective By combining the EfficientNet model to study the changes in tongue images of gastric cancer,analyzing the categories of tongue color and coating color,the aim is to use a portable traditional Chinese medicine intelligent tongue diag-nostic instrument to assist doctors in making more accurate diagnosis and treatment decisions.Statistical techniques are used to an-alyze quantitative indicators of different tongue and coating colors.Method Collect tongue image data from 5000 subjects,and use BP neural network and convolutional neural network to classify tongue color and coating color in the control group,respectively.The observation group combined EfficientNet model with BP neural network and convolutional neural network to classify tongue color and coating color respectively,in order to analyze the changes in tongue images of gastric cancer patients,and used evalua-tion indicators to evaluate the effectiveness of the model.Result The observation group model was used to study the changes in tongue images of gastric cancer,with an accuracy rate of 96.59%.The recall rate,accuracy rate,and accuracy rate of identif-ying moss color in the test set are 92.63%,92.62%,and 90.60%,respectively.The recall rate,accuracy rate,and accuracy rate of tongue color recognition are 89.61%,88.62%,and 88.45%,respectively.Conclusion The EfficientNet network model can improve the efficiency of identifying changes in tongue color and coating color,which provides strong support for improving the efficiency of clinical doctors in diagnosis and treatment decision-making.
关键词
胃癌/舌像变化/EfficientNet/舌色/苔色/精确率
Key words
Gastric cancer/Changes in tongue image/EfficientNet/Tongue color/Moss color/Accuracy
维普
万方数据