Diabetes typing method and device

A typing method and diabetes technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as standardization defects in promotion and typing

Inactive Publication Date: 2017-09-01
广州普麦健康咨询有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, some TCM studies now classify type 2 diabetes into phlegm-dampness constitution, yin-deficiency constitution, stasis constitution, qi-deficiency constitution, etc. according to TCM constitution.

Method used

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  • Diabetes typing method and device
  • Diabetes typing method and device

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0085] Our test group is composed of 213 patients from a certain hospital who have been diagnosed with type 2 diabetes. 213 subjects did not have typical features of typical type 1 diabetes and other types of diabetes. The subjects had to fast overnight for 10h-12h, and take venous blood on an empty stomach in the morning of the next day, and measure fasting blood glucose (FG) and glycosylated hemoglobin (HbA1c) on the same day; take serum and store it in a -80°C refrigerator for unified Other indicators were detected, including fasting proinsulin (FPI), fasting insulin (FI), and fasting C-peptide (C-peptide). Unless otherwise specified, conventional equipment and methods are used, and the specific detection methods are as follows:

[0086] 1. The detection of blood glucose and glycosylated hemoglobin is completed by ADVIA2400 automatic biochemical analyzer;

[0087] 2. Serum insulin and proinsulin were detected by biotin-avidin double-antibody sandwich enzyme-linked immunos...

Embodiment 2

[0096] The K-means clustering algorithm is used to perform cluster analysis on 213 diabetic patients. The K-means clustering algorithm is a clustering algorithm that uses distance as a similarity evaluation index. If the distance between two objects is closer, the similarity is greater. Big. K-means clustering algorithm considers that clusters are composed of close objects, so compact and independent clusters will be obtained as the final goal. The K-means clustering algorithm has many advantages such as the calculation time complexity is close to linear, and is suitable for the mining of large-scale data sets. Therefore, the K-means clustering algorithm is adopted as a real situation to verify the scientificity of the diabetes typing method disclosed in the present invention.

[0097] Principal component analysis (PCA) is a statistical method that uses the idea of ​​dimensionality reduction to convert multiple indicators into a few comprehensive indicators. Its function is t...

Embodiment 3

[0101] Adopt diabetes typing method of the present invention to carry out typing to 213 diabetic patients of embodiment 1, then carry out PCA analysis to typing result, carry out dimension reduction drawing by PCA, and represent different typing by different label symbols, can It is obvious that there are 6 major subgroups, such as image 3 shown. From image 3 It can be seen that the typing result of the present invention is very similar to the result of k-means clustering typing after PCA analysis after PCA analysis.

[0102] In order to calculate the similarity between the k-means clustering type and the diabetes typing method of the present invention, the coincidence degree is used for calculation, and the coincidence degree refers to the part where the distribution of the quality characteristic value and the distribution of the expected value coincide with the total quality characteristic value The ratio of the distribution. The coincidence degree between the diabetes ...

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Abstract

The invention belongs to the field of disease typing and particularly relates to a diabetes typing method and device. The diabetes typing method comprises the steps of acquiring a fasting blood glucose content value, a glycosylated hemoglobin content value, a fasting insulin original content value, a fasting C-peptide content value, a fasting insulin content value, a pancreatic beta cell function level indicator value and an insulin resistance level indicator value of a type-II diabetic and obtaining a typing result through a preset diabetes typing model. Through the diabetes typing method and device, the technical defect that a precise and fast diabetes assistant typing method and device are lacked currently is overcome. Through the diabetes typing method and device, the type-II diabetic can be typed accurately, and the highest typing accuracy is 90% or above.

Description

technical field [0001] The invention belongs to the field of auxiliary treatment of diabetes, in particular to a method and device for typing diabetes. Background technique [0002] With the improvement of living conditions in recent years, the incidence of diabetes is getting higher and higher, accounting for a larger proportion of the total population. According to the statistics of the International Diabetes Federation (IDF), in 2011, there were 370 million people with diabetes in the world, 80% of whom were in developing countries; it is estimated that by 2030, there will be nearly 550 million people with diabetes worldwide. As a country with a large population, the number of people suffering from diabetes in my country has tripled in the past 20 years. If this trend develops, China will likely become the country with the largest number of people with diabetes in the world. The disability and fatality rate of complications caused by diabetes will generate huge medical ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 陈龙钟志然廖思茵刘蓉顾炜
Owner 广州普麦健康咨询有限公司
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