Design And Implementation Of Intelligent Diagnostic Guide Question Answering System

With the rapid development of society and economy,people pay more and more attention to health problems while their living standards are improving steadily.Especially with the ravaging of COVID-19 in 2020,people have a deeper understanding of health.The need for health facilities is becoming more and more urgent.However,due to the lack of knowledge of medical diseases,the lack of understanding of the hospital departments,resulting in errors in registration and resulting in light is a waste of time heavy delay in the case of the disease is common.Although some hospitals have consultation and guidance staff,the limited number of staff often leads to difficulties in responding to patients’ questions in time.Many patients query relevant disease and outpatient information through the Internet search engine before admission.But the engine search is difficult to understand the accurate intention of the patients,and the lengthy document information is returned,and the patients need to be screened again.With the rapid development of Internet and artificial intelligence technology,the intelligent guidance Q&A system for outpatient halls in hospitals can be designed and implemented with the help of new technologies such as knowledge graph,semantic analysis and machine learning,which can effectively solve the above problems and promote the development of intelligent medical field.This topic mainly starts from the current medical service status and puts forward a set of intelligent guidance question-answering system construction scheme for the construction and storage of medical knowledge map and semantic analysis of intelligent guidance question-answering system.The main work of this paper includes the following aspects:1.Investigated the needs of hospital patients and analyzed the feasibility of the system.Clarify the goals of the intelligent guidance system.Put forward the overall design and implementation of the system,and reasonable planning of the functions of each module.2.Building a small medical knowledge map.The required data were extracted from various medical websites by web crawlers.Knowledge extraction in the medical field was carried out by rule dictionary method.Medical knowledge atlas was constructed by writing rule statements into Neo4 j graph database.3.Design and implement an intelligent consultation question-answering system based on medical knowledge map.Implement semantic analysis on input questions,extract keywords and categorize questions.Using Cypher language to write the query template and retrieve the generated question answers.Design disease prediction inference model.Based on the medical knowledge graph and Neo4 j graph database,the similarity of disease symptoms is calculated by the disease prediction algorithm and the best answer is recommended,so as to realize the intelligent question and answer function and intelligent consultation function of the system.4.Use Qt model to package the whole system and complete the human-computer interaction interface.Users realize human-computer interaction with the system in the form of natural language dialogue to obtain the information they want to query.Finally,intelligent question and answer,disease prediction and department guidance functions are realized.The function and performance test results show that the system reaches the expected indicators,can provide patients with good medical knowledge question-andanswer service,effectively replace manual to improve efficiency,optimize resource allocation,and provide patients with better guidance results to improve medical experience.The system has high accuracy,good performance and short response time,so it has high application value and application prospect.