Intelligent diagnosis auxiliary system based on medical knowledge graph

Abstract

The invention discloses an intelligent diagnosis auxiliary system based on a medical knowledge graph, and belongs to the field of medical diagnosis. In order to solve the problems that a traditional medical diagnosis system is difficult to integrate information, a large amount of medical information is wasted, effective auxiliary diagnosis cannot be carried out, the doctor seeing efficiency is low, effective intelligent triage prediction cannot be carried out, doctor seeing burdens and hospital operation burdens are easily generated for patients, the working efficiency is low, and the work efficiency is high. And a corresponding treatment result cannot be timely and quickly given, so that the diagnosis accuracy is influenced. The problem of existing medical data islands is solved, intelligent auxiliary diagnosis of common diseases is achieved, the doctor seeing efficiency is improved, high-credibility auxiliary diagnosis is provided for doctors, intelligent triage prediction is achieved, the probability of wrong triage is reduced, efficient and convenient pre-diagnosis consultation is provided for patients, the burden of the patients and the operation load of hospitals are relieved, and the patient experience is improved. The diagnosis accuracy of the auxiliary system for comprehensive data analysis and diagnosis of patient information is gradually improved through artificial error correction.

Description

technical field [0001] The invention relates to the field of medical diagnosis, in particular to an intelligent diagnosis auxiliary system based on a medical knowledge graph. Background technique [0002] The medical field is a data-intensive, knowledge-intensive, and mental-labor-intensive field. The massive amount of data that is continuously generated in the medical industry is mostly unstructured data. With the continuous improvement of my country's medical system, medical resources, including medical equipment and medical staff, are also gradually growing. However, the shortage of medical resources, the inefficiency of hospital operation still exist, the distribution of domestic medical resources is uneven, and the original disease diagnosis The method is often constrained by the actual experience of the decision maker, and is easily disturbed by the decision maker's subjective consciousness and the external environment at that time, so the diagnosis results will be bia...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide an intelligent diagnosis auxiliary system based on medical knowledge map. By establishing electronic medical records of patients, it can reduce the burden of doctors entering medical records. The problem of isolated islands improves the utilization rate of medical data and realizes the intelligent auxiliary diagnosis of common diseases. It is convenient for patients to find characteristic diseases in time when they seek medical treatment, which improves the efficiency of medical treatment and brings convenience to patients. Through the automatic diagnosis module Corresponding diagnosis, so as to analyze and obtain suspected diseases with weight, provide doctors with high reliability auxiliary diagnosis, help improve doctor's diagnostic efficiency and accuracy, realize intelligent triage prediction, reduce the probability of wrong triage, and provide patients with Provide efficient and convenient pre-diagnosis consultation, reduce the burden on patients and hospital operation, bring patients an efficient and accurate medical experience, and ensure that after considering more influencing factors, it can give more objective and reliable diagnosis system than the existing artificial intelligence diagnosis system Diagnosis and treatment opinions avoid the complexity of user input information and the trouble of insufficient equipment in the user's environment, and users can conduct intelligent diagnosis and treatment of diseases anytime, anywhere as long as there is a network, and gradually improve patient information through human error correction Carry out comprehensive data analysis on the diagnosis accuracy rate of the diagnostic assistance system to solve the problems raised in the above-mentioned background technology

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