Thoughts and Methods about Deep Learning Model of Thenar Inspection for Coronary Heart Disease Patients Based on Deep Convolutional Neural Network and Prior Knowledge
Inspection of traditional Chinese medicine(TCM)based on the holographic theory can assist in the diagnosis of Western diseases.However,the current TCM inspection mainly relies on the experience of famous and old experts,and there is the problem of insufficient objectification and standardization of inspection,and the lack of a highly recognized inspection transfor-mation technology in the industry.The integration of inspection with artificial intelligence information technology can enhance the objectivity and standardization of TCM inspection,which can effectively reduce the deterioration rate and mortality of diseases and promote the transformation of TCM inspection experience.Taking the relationship between large fissure lookout and coronary heart disease(CHD)as an example,the prior knowledge and deep convolutional neural network algorithm are deeply fused to combine feature extraction and classification into one,using the significant features of deep learning end-to-end,inputting the observed pixel data or information of the original large fissure image,constructing the key feature elements of CHD patients through exten-sive deep learning of large fissure photos,and outputting after fusing the prior knowledge whether it is the classification result of CHD,and the middle is the deep network structure.This idea will propose an intelligent algorithm for the objectification and standardization of TCM inspection,promote the transformation of TCM inspection,improve grassroots people s ability of disease early warning and screening,and serve the strategy of"Healthy China".
万方数据
维普
