Research And Realization Of Medical Case Automatic Generation Based On Named Entity Recognition

In recent years,with the continuous development of "Internet+ medical" technology,the management of hospitals is more automated and networked,and the traditional manual paper medical records are being replaced by electronic medical records.Electronic medical records can transmit information more quickly,making the diagnosis and treatment process more convenient and easy to manage.Through years of development,the usage of electronic medical records have been gradually expanded in practical applications.At present,although the major hospitals have already put into the use of electronic medical record system,in most cases it still need the doctors to operate step by step,and sometimes even use manual medical record entry system,there is no really effective reduction of the workload of doctors.Especially for senior doctors,cumbersome operation will also affect work efficiency.Therefore,in order to simplify the work of doctors’ medical records,this paper studies the automatic generation system of electronic medical records.In this paper,the author studies on electronic medical records automatically generatedby named entity recognition technology,propose the named entity recognition method based on neural network(BILSTM·CRF)on the extraction of symptoms and disease model of important medical data such as training.By comparing the effect of word and character level BILSTM-CRF model,more suitable for named entity recognition of medical text input methods are choosed;The method of short text classification is used to predict the unknown symptoms and predict their disease category.By comparing the classification effect of textCNN classification algorithm and textRNN classification algorithm,this paper explores the advantages and disadvantages of the two classification algorithms in the application process,and selects the better classification algorithm to be implemented in the system.Then it introduces the formulation of medical record template and summarizes the specific information contained in outpatient medical record.By analyzing a large number of outpatient medical records information,the structure between different levels is summarized,and an electronic medical record template is created.Finally,the method of rule matching is used to automatically generate medical records,and the medical records automatic generation system is realized.