Method and system for predicting dynamic morbidity risk of cardiovascular complication of diabetes mellitus patient

A diabetes and cardiovascular technology, applied in the field of predicting the risk of disease, can solve problems such as the inability to dynamically predict the risk of individual cardiovascular disease, and achieve the effect of preventing and preventing the development of the disease, reducing the occurrence, and promoting the outcome.

Active Publication Date: 2020-06-19
SUZHOU UNIV
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  • Abstract
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Problems solved by technology

[0004] For this reason, the technical problem to be solved by the present invention is to overcome the problem in the prior art that it is impossible to dynamically predict the risk of cardiovascular disease for individuals, thereby providing a method for dynamically predicting the risk of cardiovascular disease for individuals, so as to prevent and prevent the development of the disease. Objective Method and system for predicting the dynamic risk of cardiovascular complications in diabetic patients

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  • Method and system for predicting dynamic morbidity risk of cardiovascular complication of diabetes mellitus patient
  • Method and system for predicting dynamic morbidity risk of cardiovascular complication of diabetes mellitus patient

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Embodiment 1

[0021] Such as figure 1 As shown, the present embodiment provides a method for predicting the dynamic morbidity risk of cardiovascular complications in diabetic patients, comprising the following steps: Step S1: collecting and integrating public health data of diabetic populations from multiple health systems; Step S2: constructing a shell Step S3: Use the evaluated model to predict the individual.

[0022] The method for predicting the dynamic risk of cardiovascular complications in diabetic patients described in this embodiment, in the step S1, collects and integrates public health data of diabetic populations from multiple health systems, which is beneficial to the complications applicable to Chinese diabetic populations Prediction; in the step S2, construct a Bayesian multivariate joint model and evaluate the model, so as to facilitate the dynamic prediction of cardiovascular disease risk for individuals, so as to achieve the purpose of preventing and preventing the develo...

Embodiment 2

[0032] Based on the same inventive concept, this embodiment provides a system for predicting the dynamic risk of cardiovascular complications in diabetic patients. The principle of solving the problem is similar to the method for predicting the dynamic risk of cardiovascular complications in diabetic patients. No longer.

[0033] The system for predicting the dynamic risk of cardiovascular complications in diabetic patients described in this embodiment includes:

[0034] A data collection module to collect and integrate public health data on diabetes populations from multiple health systems;

[0035] Constructing a model module for constructing a Bayesian multivariate joint model and evaluating said model;

[0036] The prediction module uses the evaluated model to make predictions for individuals.

[0037] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly,...

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Abstract

The invention relates to a method and a system for predicting a dynamic morbidity risk of the cardiovascular complication of a diabetes mellitus patient. The method comprises the following steps of: collecting and integrating the public health data of a diabetes mellitus crowd from a plurality of health systems; constructing a Bayes multivariable combined model, and evaluating the model; and utilizing the evaluated model to predict an individual. According to the method, a purpose of preventing and stopping progression of diseases can be achieved.

Description

technical field [0001] The present invention relates to the technical field of morbidity risk prediction, in particular to a method and system for predicting the dynamic morbidity risk of cardiovascular complications in diabetic patients. Background technique [0002] Since the 1970s, many countries and regions have carried out large-scale studies on cardiovascular disease risk factors, and successively introduced a number of cardiovascular disease risk assessment methods, such as the British prospective diabetes prediction model, which uses Cox The proportional hazards model is established to predict the risk of coronary heart disease in patients with type 2 diabetes through the gender of diabetic patients, age at diagnosis of diabetes, smoking status, and the values ​​​​of systolic blood pressure, cholesterol, low-density lipoprotein, and glycated hemoglobin. Health economists, A software package that makes the model freely available to clinicians and diabetics alike. [...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00
CPCA61B5/7275A61B5/7246Y02A90/10
Inventor 孙宏鹏王从菊崔志贞曹桂珍
Owner SUZHOU UNIV
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