Method for constructing disease prognosis risk assessment model based on causal reasoning

A risk assessment model, disease technology, applied in the field of data processing, can solve the problem of lack of generality of scoring tools

Active Publication Date: 2020-04-03
GENERAL HOSPITAL OF PLA +1
View PDF18 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] These tools have been used in clinical practice, but still have the following limitations. Only a small number of features are used as risk factor...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for constructing disease prognosis risk assessment model based on causal reasoning
  • Method for constructing disease prognosis risk assessment model based on causal reasoning
  • Method for constructing disease prognosis risk assessment model based on causal reasoning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0076] Example 1 to obtain the evaluation model

[0077] 1. Model acquisition steps

[0078] The model samples come from 736 patients with heart failure, and the 736 patients with heart failure are provided by the General Hospital of the Chinese People's Liberation Army, excluding private information such as names. In the entire dataset, there were 461 patients who were readmitted within one year, accounting for 62.6% of the total sample number.

[0079]1. Extract the characteristics of 736 patients with heart failure, mark whether to be admitted to the hospital again within one year, and use it as a true value label to obtain a training sample with a true value label, wherein the features are selected from physical signs (such as age, height, body weight, etc.), inspection and test information (such as red blood cell count, white blood cell count, etc.), disease course report, drug (such as aspirin, etc.) use records, whether to be re-admitted within one year, past medical h...

Embodiment 2

[0094] A total of 736 heart failure patient case data used in this example were provided by a tertiary hospital in China, excluding private information such as names. In the whole dataset, there were 461 patients who were readmitted within one year, accounting for 62.6% of the total sample number.

[0095] Carry out training according to embodiment 1 step flow process:

[0096] In order to better compare the superiority of the model proposed by the present invention, the accuracy of the model in predicting patient readmission within one year is compared. In this embodiment, the data is divided into training set, verification set and test set according to the ratio of 0.56, 0.24, and 0.20, and then the experiment is repeated 100 times to compare with the benchmark models BART, CFR_mmd, CFB_lin and CFR_wass. From the accuracy rate (ACC), compare the pros and cons of several models. Table 1 shows that compared with the models described in the present invention, our model has ac...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a method for constructing a disease prognosis risk assessment model based on causal reasoning and a disease prognosis risk assessment system based on causal reasoning. Based oncausal reasoning, the probability of re-admission of a patient with cancer or cardiovascular and cerebrovascular diseases within one year is predicted by utilizing a full-connection neural network, and the effects of different treatment schemes are evaluated, so that doctors are assisted in making reasonable diagnosis and treatment measures, supporting clinical decisions and reducing medical expenditure.

Description

technical field [0001] The present invention relates to the technical field of data processing, and in particular to a method for evaluating a prognosis risk assessment model of cancer or cardiovascular and cerebrovascular diseases based on causal reasoning and a system for assessing prognosis risk. Background technique [0002] Heart failure, referred to as heart failure, refers to the failure of the venous blood to fully discharge the heart due to cardiac systolic and / or diastolic dysfunction, resulting in blood stasis in the venous system and insufficient blood perfusion in the arterial system, resulting in cardiac circulation syndrome. , This kind of disorder symptom group manifests as pulmonary congestion and vena cava congestion. Heart failure is not an independent disease, but the end stage of the development of heart disease. The vast majority of heart failures begin with left heart failure, that is, the first manifestation is pulmonary circulation congestion. [0...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G16H50/30G16H50/20G06N5/04
CPCG16H50/30G16H50/20G06N5/04Y02A90/10
Inventor 何昆仑黄正行白永怿刘宏斌边素艳贾倩
Owner GENERAL HOSPITAL OF PLA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap