Automatic MELD scoring method, terminal and storage medium

A technology for analyzing data and population information, applied in the field of big data processing, it can solve problems such as the inability of unified integration of data, inconsistent data standards between systems, and inability to automate data extraction.

Pending Publication Date: 2021-07-06
福州宜星大数据产业投资有限公司 +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the inconsistency of the database types used by these systems and the inconsistency of data standards between systems, these data cannot be integrated in a unified way in the existing technology
The MELD scoring tool in the prior art is manually input by the doctor, and then judged according to the rules in the background, which cannot automatically extract the required data

Method used

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  • Automatic MELD scoring method, terminal and storage medium
  • Automatic MELD scoring method, terminal and storage medium
  • Automatic MELD scoring method, terminal and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] Such as figure 1 Shown, is the automatic MELD scoring method step flowchart of the present invention, comprises the following steps:

[0046] Step S1, obtaining analysis data from the hospital information system, electronic medical record system, and laboratory examination information system; the analysis data includes population information, clinical diagnosis data, and test data; the population information includes outpatient population information and inpatient population information;

[0047]Because the MELD score needs the support of demographic information, diagnosis, and test data, these data are usually scattered in various hospital information systems such as the hospital information system HIS, the electronic medical record system EMR, and the laboratory examination information system LIS. Since the types of databases used by these systems may be inconsistent, and the data standards between systems may be inconsistent, therefore, in order to use these data for...

Embodiment 2

[0075] This embodiment also provides a kind of automated MELD scoring terminal, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a cabinet server (including an independent server) that can execute a program. , or a server cluster composed of multiple servers), etc. Such as Image 6 Shown is a structural diagram of the automated MELD scoring terminal of the present invention. The terminal of this embodiment includes at least but not limited to: a memory and a processor that can communicate with each other through a system bus. In some embodiments, the memory can be an internal storage unit of the automated MELD scoring terminal, such as the hard disk or internal memory of the automated MELD scoring terminal, or an external storage device of the automated MELD scoring terminal, such as the one equipped on the automated MELD scoring terminal. Plug-in hard disk, smart memory card, etc. The process...

Embodiment 3

[0077] The technical solution of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to realize Any of the steps above to automate the MELD scoring method.

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Abstract

The invention relates to the technical field of big data processing, in particular to an automatic MELD scoring method, a terminal and a storage medium. The method comprises the following steps: obtaining population information, clinical diagnosis data and inspection data from a hospital information system, an electronic medical record system and a laboratory inspection information system; preprocessing the population information to obtain patient index number information; carrying out structured analysis on the clinical diagnosis data to obtain pathogenesis of the hepatopathy; screening serum total bilirubin, serum creatinine and international standardized ratio data from the test data; summarizing patient index number information, clinical diagnosis data and inspection data; and calculating the summarized data according to an MELD scoring rule to obtain an MELD scoring result of each patient. According to the method, data dispersed in different databases are normalized and unified, perfect and accurate MELD scoring data are provided, an automatic calculation model is constructed for MELD scoring, an accurate scoring result is obtained, the working efficiency can be improved, and the evaluation accuracy can be improved.

Description

technical field [0001] This application relates to the technical field of big data processing, in particular to an automatic MELD scoring method, a terminal and a storage medium. Background technique [0002] World Health Organization (WHO) report in 2017 shows that there are an estimated 340 million viral hepatitis infections worldwide. Another survey shows that about 25% of the general population suffers from non-alcoholic fatty liver disease, and about 4.5% to 9.5% suffer from liver cirrhosis. End-stage liver disease is the main cause of death of chronic liver disease, and it is the advanced stage of liver disease caused by various chronic liver damage. About 770,000 people die of liver cirrhosis every year, which poses a serious threat to people's health and life. [0003] The Model for End-Stage Liver Disease (MELD) score is a scoring system to evaluate the liver function reserve and prognosis of patients with chronic liver disease based on serum total bilirubin, inte...

Claims

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Application Information

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IPC IPC(8): G16H50/20G16H50/70G16H10/60
CPCG16H50/20G16H50/70G16H10/60
Inventor 刘景丰黄起桢方建凯李海涛郭鹏飞刘红枝林孔英丁宗仁陈传椿李保晟
Owner 福州宜星大数据产业投资有限公司
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