Research Of Intelligent Hepatopathy Auxiliary Diagnosis System Based On Text Semantic Analysis Of Electronic Medical Records

At present,liver disease has become one of the most fatal diseases in the world,and it is difficult to diagnose because its early pathological symptoms are not very obvious.At the same time,there is still no unified structure and standard in electronic medical data,especially the electronic text data,which has a lot of redundancy and ambiguity.And there are many barriers between medical institutions as well so that electronic medical data can’t be interconnected.With the development of mobile communication technology and medical information technology,electronic medical data is accumulating rapidly.Rational use of electronic medical records can reduce the rate of misdiagnosis of liver disease.Text processing technology enables text data to be reasonably expressed as digitalized features,and abstracts the semantic information contained in it by learning and training text data,which can assist the doctor’s diagnosis and treatment.This paper analyzes the characteristics of the text data in the electronic medical record of liver disease,and applies the word embedding technology and the deep learning theory to the processing of the electronic medical record.In view of the limitation of ignoring global information of the document in the word embedding training,this paper adds the full-text word co-occurrence statistics so that the word embedding can retain more semantic information.For the shortcomings of traditional disease prediction based on feature extraction and classifier,this paper puts forward a fixed length matrix representation of medical text data by using the idea of partial processing of image data,and combines the PeNet network model and the improved Yoon network model to get an integrated model using ensemble learning,which has achieved good results in the classification of electronic medical records.Based on the previous results,this paper implements an intelligent hepatopathy auxiliary diagnosis system based on text semantic analysis of electronic medical records,which provides functions such as disease prediction,key information extraction,intelligent speech conversion,similar data matching,user and medical data management.And to some extent,it implements the artificial intelligence of electronic medical data processing.The system is divided into three parts,the web page,the mobile terminal and the backstage server.Each part is decoupled and separated,and the data interaction is carried out through the Internet.The test proves that the system has good concurrency performance and the ability to work under weak network conditions.