Method and system for disease prediction model building based on glycometabolism data

A prediction model and construction method technology, applied in the field of big data analysis, can solve the problems of inaccurate analysis of data, weak model accuracy and generalization ability, and inability to apply prediction equipment, so as to improve accuracy and generalization ability and reduce training Effects on error and training time, increasing effectiveness and accuracy

Pending Publication Date: 2021-08-13
FUZHOU UNIV
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Problems solved by technology

The existing traditional systems and models cannot accurately analyze the corresponding data and realize data prediction, and the model accuracy and generalization ability are weak, so they cannot be applied to existing prediction equipment

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  • Method and system for disease prediction model building based on glycometabolism data

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] Please refer to figure 1 , this embodiment provides a method for constructing a disease prediction model based on glucose metabolism data, including the following steps:

[0027] Step S1: Obtain the glucose metabolism data of the sample population, which contains a total of 72 variables to form the first sample set, and construct the first sample data set;

[0028] Step S2: Carry out data cleaning and standardization on the first sample set according to the disease knowledge base corresponding to the routine examination data of glucose metabolism, and simultaneously perform characteristic variable screening, remove irrelevant variables, and the remaining 32 variables constitute the second sample set;

[0029] Step S3: The second sample set is sorted and screened by the LightGBM algorithm for feature importance, and the top N important features a...

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Abstract

The invention relates to a method for disease prediction model building based on glycometabolism data, and the method comprises the following steps: S1, obtaining the glycometabolism data of a sample population, and constructing a first sample data set; S2, preprocessing the obtained initial sample data set to obtain a second sample set; S3, sorting and screening the second sample set according to feature importance through a LightGBM algorithm, extracting the top N ranked importance features to form a third sample set, and dividing the third sample into a training set and a verification set according to a preset proportion; S4, taking the training set as an input of a LightGBM model, training the LightGBM model until the deviation between the output value of the LightGBM model and the true value is lower than a threshold value, and obtaining a disease prediction model. The method can effectively improve the model precision and generalization ability, the probability that a to-be-detected person suffers from the diseases related to the abnormal glucose metabolism can be rapidly predicted, and the strain on medical resources is eased.

Description

technical field [0001] The invention relates to the field of big data analysis, in particular to a method and system for constructing a disease prediction model based on glucose metabolism data. Background technique [0002] In my country, type 2 diabetes is the main type of diabetes. In the 2013 national survey, the prevalence of type 2 diabetes was 10.4%, and men were higher than women (11.1% vs. 9.6%). Type 2 diabetes is the main type of diabetes, and the danger lies in its complications. Diabetes and its complications have become the main cause of death and disability among the population, and seriously threaten people's health. It should be noted that type 2 diabetes is a preventable and controllable chronic disease, and its development often takes a period of time. Due to the complexity and multifactorial nature of diabetes and prediabetes, the prevention of diabetes and prediabetes must refer to multiple risk factors. However, it can be difficult to assess a person...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/70G06K9/62G06N20/00
CPCG16H50/30G16H50/70G06N20/00G06F18/214G06F18/241
Inventor 何炳蔚陈斌赫韩东趣杨旭华
Owner FUZHOU UNIV
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