Complication onset risk prediction method and system based on electronic medical record big data, terminal and storage medium

An electronic medical record and risk prediction technology, which is applied in the mining and application of medical big data, can solve the problems of coronary heart disease risk factors and text information that are rarely studied and expensive, so as to improve machine processing speed, improve work efficiency, and save money. The effect of medical costs

Pending Publication Date: 2020-09-25
SHENZHEN INST OF ADVANCED TECH
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Problems solved by technology

However, the combination of classical CHD risk factors and textual information has rarely been studied
Clinically, doctors usua

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  • Complication onset risk prediction method and system based on electronic medical record big data, terminal and storage medium
  • Complication onset risk prediction method and system based on electronic medical record big data, terminal and storage medium
  • Complication onset risk prediction method and system based on electronic medical record big data, terminal and storage medium

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Embodiment Construction

[0058] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, not to limit the present application.

[0059] see figure 1 , is a flow chart of the method for predicting the risk of complications based on electronic medical record big data according to the first embodiment of the present application. The method for predicting the risk of complications based on the big data of electronic medical records in the first embodiment of the present application includes the following steps:

[0060] Step 100: collecting electronic medical record data of the population with the same primary disease, and preprocessing the electronic medical record data to obtain usable electronic medical record data;...

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Abstract

The invention relates to a complication onset risk prediction method and system based on electronic medical record big data, a terminal and a storage medium. The method comprises the steps: collectingelectronic medical record data of the same primary disease crowd, wherein the primary disease crowds comprise primary disease crowds with related complications and primary disease crowds without complications; extracting features related to the complications of the primary disease from the electronic medical record data, and selecting features with significant differences from the extracted features by adopting a normal distribution test; classifying the features with significant differences to form a data set for constructing a model; and constructing a complication onset risk prediction model of the primary disease according to the data set. The method has no side effect on patients, has certain technical intensification, can greatly improve the machine processing speed, improves the working efficiency of doctors, and can save the medical cost.

Description

technical field [0001] The application belongs to the technical field of mining and application of medical big data, and in particular relates to a method, system, terminal and storage medium for predicting the risk of complication based on big data of electronic medical records. Background technique [0002] Complications are a complex concept in clinical medicine. Scholars define complications as follows: one refers to the occurrence of another disease or symptom caused by one disease during the development process, and the latter is the complication of the former, such as peptic ulcer may have pyloric obstruction, Complications such as gastric perforation or massive bleeding. Another kind of complication refers to the combination of one disease and another disease or several diseases related to this disease in the course of diagnosis and treatment. Taking coronary heart disease as an example, in some epidemiological studies, typical unmodifiable risk factors for coronar...

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Application Information

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IPC IPC(8): G16H50/30G16H50/70G16H10/60
CPCG16H50/30G16H50/70G16H10/60
Inventor 梁升云赵国如张宇
Owner SHENZHEN INST OF ADVANCED TECH
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