Clinical decision support system and decision-making method

Abstract

The invention discloses a clinical decision support system and a decision-making method and belongs to the field of medical artificial intelligence. The clinical decision support system and the decision-making method are provided to solve the problems that in the prior art, existing decisions are made for a special discipline, the correct rate of data diagnosis is still not high, and the resource sharing degree is low. The system comprises a medical knowledge base, an inference machine, an interpreter and a human-computer interaction module providing an interaction platform for patients and doctors. According to the method, after a doctor selects symptom characteristics, the symptom characteristics are input into the internal inference machine, information of a possible disease of a patient and the probability of the disease are calculated, then a doctor client refreshes a new to-be-inquired symptom problem and displays the probability of the disease to the doctor through a chart, and an interpretation module on a page can display interpretation of the possible disease. Through the clinical decision support system and the decision-making method, clinical decision support for primary medical symptoms can be realized, the decision level is increased, and the correct rate of data diagnosis is high.

Description

technical field [0001] The present invention relates to the field of medical artificial intelligence, and more specifically, relates to a clinical decision support system and a decision method. Background technique [0002] With the continuous development of social economy and the transformation of medical models, the people are more and more concerned about their own health. How to improve our health level and how to ensure a high-quality, low-cost, low-risk medical service are increasingly concerned The problem. In clinical diagnosis and treatment, no matter how common or complicated the case is, doctors may make mistakes in diagnosing patients or even lead to misdiagnosis. In the process of clinical diagnosis, doctors rely on the accumulation of personal professional knowledge and clinical experience to provide services for patients. However, due to closed factors, the knowledge of clinicians cannot be synchronized with the constantly updated medical knowledge, and an e...

AI Technical Summary

Problems solved by technology

[0006] (1) The existing medical expert database is a two-layer model, and the correct rate of disease diagnosis is low;

[0007] (2) The uncertainty of knowledge base representation;

[0008] (3) The existing CDSS is expensive and cannot be maintained;

[0009] (4) It is difficult to manage massive data;

[0010] (5) The existing CDSS is a stand-alone mode, unable to communicate and share resources;

[0011] (6) Most of the existing CDSS are specialized and cannot meet normal clinical use

This invention is based on a structured evidence-based knowledge base, introduces omics variation, supports clinical decision-making from the gene level, covers DNA, RNA, protein, metabolome and epigenetic level variation, through the analysis of omics variation data and evidence-based annotation, Provide reference information for clinical decision-making, improve the accuracy and reference of clinical decision-making support, but this invention still makes decisions on specialist aspects, and the correct rate of data diagnosis is still not high, and the degree of resource sharing is poor

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