Design And Implementation Of Intelligent Diagnosis Guidance System Based On Deep Learning

Offline hospitals take a long time to queue and the cumbersome process of seeing a doctor is already a pain point in every patient’s heart.Although almost every hospital has its own system that provides online appointment registration,offline medical treatment,or direct online consultation,etc.,patients still need to choose a department based on their own characteristics and find a doctor,but this way It shows that the Internet hospital data is not fully utilized.Therefore,the use of deep learning technology to solve people’s rapid online medical treatment has become an urgent problem.In order to effectively optimize the allocation of medical resources in domestic hospitals,improve the quality of medical services in domestic hospitals,and improve the medical treatment rate and efficiency of medical treatment for the majority of patients.Better give full play to the management power of offline doctors,make full use of the hospital’s existing offline hospital management information,doctors’ personal information,and the latest offline deep machine learning management technology to establish an online and offline smart hospital guidance management system.The main functions of the diagnosis guidance system include the following main functions: The current main consultation function for offline patients is to have extremely fast online consultation,intelligent online consultation,search to find your doctor,and your hospital.The doctor-oriented functions mainly include reception and other functions.According to the patient’s description information,the condition can be automatically identified and assigned to a specific department.However,in this process,the traditional hospital registration,queuing,waiting and other complicated processes are eliminated.It greatly improves the efficiency of medical treatment,shortens the time in the hospital,reduces the burden of the medical guide,and reduces the labor intensity of the hospital staff.After in-depth understanding and analysis of the current problems,in order to solve these problems,the author studied the algorithm model of intelligent triage and developed an intelligent diagnosis guidance system.The algorithm model and the system respectively solve and study the following problems.(1)Feature research on text sparse representation,which solves the problems of insufficient short text information,difficulty in feature extraction,and difficulty in understanding semantics.(2)Research on the fusion training model of joint knowledge,by summarizing the advantages and disadvantages of predecessor models,and absorbing the crystallization of the wisdom of predecessors,based on the special scenarios of smart medical care,a fusion training model is proposed,which not only solves the problem of traditional model,the problem of slow training,the accuracy rate has also improved.(3)The engineering technology research of the intelligent diagnosis guidance system,in addition to the improvement of the algorithm,also proposed a novel interactive design in the system experience,and improved the traditional hospital appointment,registration,queuing and so on by the way of rapid and intelligent consultation.Greatly improve efficiency.