Medical decision system based on medical big data and artificial intelligence

Abstract

The invention provides a medical decision-making system based on medical big data and artificial intelligence, which belongs to the technical field of medical data mining and specifically comprises a medical big data system, a data uploading module and a hospital system. The medical big data system is responsible for processing the uploaded data of the data uploading module, generating symptom keywords of a patient to be treated, performing similarity matching on the symptom keywords of the patient to be treated and symptom keywords of historical clinical symptoms, and obtaining similar diagnosis and treatment cases; extracting clinical diagnosis and treatment inspection information data, and matching the clinical diagnosis and treatment inspection information data with the clinical diagnosis and treatment inspection information data of the similar diagnosis and treatment cases to obtain a consistent diagnosis and treatment case; extracting clinical diagnosis and treatment image information of the patient to be treated, and matching the clinical diagnosis and treatment image information with the clinical diagnosis and treatment image information conforming to the diagnosis and treatment case to obtain a matched diagnosis and treatment case; the data uploading module is responsible for uploading the uploading data; and the hospital system is responsible for generating uploading data and pushing the matched diagnosis and treatment case to a diagnosis doctor, so that accurate and rapid medical record matching is realized.

Description

technical field [0001] The invention belongs to the technical field of medical data mining, in particular to a medical decision-making system based on medical big data and artificial intelligence. Background technique [0002] IBM officially proposed the concept of "cloud computing" in 2007. Since then, cloud computing, artificial intelligence, Internet + and other information technologies have developed rapidly. It has been applied in all walks of life and has become an indispensable part of the development process. The medical industry is one of the data-intensive industries and one of the earliest industries to realize digital informatization. Correctly and rationally using medical big data resources can enable medical institutions to make more reasonable and scientific decisions and planning. At the same time, the general population can also understand and assess their own health more easily and conveniently, maximize the use of health resources, and make people's lives...

AI Technical Summary

Problems solved by technology

[0003] Chinese Invention Patent Publication No. CN104915561B discloses a method for intelligent matching of disease characteristics. In order to solve the problem that doctors need to refer to similar cases when diagnosing, the search for similar cases means finding matching feature vectors from a huge case database. Obviously, the traditional The keyword-based search method cannot meet the technical problem of fast matching of multi-dimensional features. The existing patient data in the electronic case database is used to extract corresponding values ​​according to the pre-established disease sign set and inspection index set to form each patient. The eigenvector of , with the similarity as the weight, calculates the score of each disease sign index and inspection index of the patient to be matched, and selects the disease sign index and / or inspection index with a score contribution of more than a certain percentage after sorting as the judgment of the disease The main features are used to assist diagnosis, but the above-mentioned patents have a large amount of calculation work and slow calculation speed. In addition, for doctors, the doctor's medical knowledge reserves and accumulated experience in diagnosis and treatment largely determine the judgment of patients' symptoms , the choice of diagnosis and treatment recommendations and the degree of follow-up treatment and recovery of the patient, which leads to the inaccurate subjective judgment of the doctor on the patient's illness, which leads to deviations in the follow-up diagnosis and treatment of the patient, and increases the error in the judgment of the patient's condition and health.

[0004] Summary of existing technical problems: Case matching is computationally intensive and slow, and there is a lack of a system and method for step-by-step case matching

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