Research On Construction Of Precise Medical Guidance Model For Online Consultation Platform

Health is the topic that everyone concerns most about.Nowadays,China's medical and health conditions have been greatly developed compared to the past.However,there are problems such as an imbalanced between supply and demand and an unreasonable distribution of medical resources in our medical industry.The party and government are concerned about the health of people.In order to improve the medical level of our country,a hierarchical diagnosis and treatment system has been proposed,and a number of related policies and programs have been introduced.Under this background,the online consultation platform,as a large-scale online medical consortium,will play an important role in the construction of the hierarchical diagnosis and treatment.The online consultation platform currently adopts a passive service model,which is harmful to the development of the online medical consortium.On the one hand,the professionalism and complexity of medical knowledge is relatively strong.In the process of choosing doctor,faced with a lot of information on the Internet,patients have the problem of "information trek",which increases the time and money costs of patients.On the other hand,patients have a blind obedience to expert doctors,resulting in insufficient high-quality medical resources,ordinary medical resources are not fully utilized,and resource allocation is uneven.In order to solve the above-mentioned problems,this article proposes a precise medicalguidance model to provide patients with intelligent and precise doctor recommendation services through information technology,and maximize the benefits of patients,hospitals and online consultation platforms.Firstly,this thesis analyzes the actual needs of doctors and patients on the online consultation platform with the object-oriented analysis method.Based on the needs of both,this article puts forward a framework of online precise medical guidance model.It is divided into an object layer and a functional layer.The object layer includes the patient model and the doctor model.The functional layer uses recommendation technology as the implementation framework to divide the precise medical guidance into department prediction,doctor-patient matching and doctor scheduling.There are three stages to meet the needs of guiding patients to choose departments,recommending suitable doctors for patients,and accurately and rationally allocate patients for doctors.Secondly,the thesis builds a patient model,integrating the personal information and medical records of patient,representing patient through textual representation.In addition,the regression analysis is used to mine the factors that affect the patient's choice,and the doctor's diagnosis and treatment characteristics and decision-making factor characteristics are merged to establish a doctor model.Then,the problem of guiding patients to choose departments is abstracted as a classification problem,and linear support vector machines are used to realize department prediction.The patient's choice is narrowed to a specific department to improve the reliability of the recommendation results.Next,based on the content-based recommendation algorithm and the idea of ??collaborative filtering,a personalized recommendation strategy was designed,and a stable matching method was adopted to realize doctor scheduling and rational allocation of doctors,to provide patients with accurate and reliable recommendations and balance the allocation of resources.Finally,implement parameter adjustment and comprehensive evaluation of this online precision guidance model.Through experiments,select the optimal parameters of the department prediction algorithm,and doctor recommendationalgorithm involved in the model,so that each module can exert its optimal effect.In addition,the performance evaluation of the model in this thesis is made from the accuracy of the department prediction,the accuracy of doctor recommendation,and the response time of doctor scheduling.Experiments find that the classification algorithm of the model in this paper has high accuracy and good generalization ability,and the prediction accuracy for ophthalmology is the highest,reaching 97%;the doctor recommendation in this paper is reasonable and the accuracy is high;the response time of scheduling in this article reaches the millisecond level,and the response speed is relatively fast.Here are the contributions of this thesis.First,it builds the framework of precise medical guidance for online consultation platform.The general consultation path of the online consultation platform is sorted out,the object-oriented analysis method is used to analyze the actual needs of doctors and patients in the process,and the model framework and implementation steps of precise medical guidance are proposed.Second,it constructs a patient model and a doctor model.Through the text representation of consultation texts and the processing of the patient's personal information,a patient model is constructed.In addition,it explores the factors that patients consider during consultation,and merges the characteristics of diagnosis and treatment and the characteristics of the decision factors to realize the doctor modeling.Third,it designs the department prediction algorithm.The thesis realize department prediction based on linear support vector machine,and clear the choice to a certain department.Fourth,this thesis puts forward a personalized recommendation strategy,integrated the content-based recommendation algorithm and collaborative filtering,and added a stable matching algorithm to achieve precise recommendation and reasonable scheduling of doctors.