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Method for constructing AI chronic kidney disease screening model and chronic kidney disease screening method and system

A chronic kidney disease, model technology, applied in the field of chronic kidney disease screening, can solve problems such as unfavorable and efficient census

Active Publication Date: 2020-08-18
SHENTAIWANG HEALTHCARE TECH NANJING CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, chronic kidney disease screening requires the examiner to conduct an examination in the hospital, which is judged by nephrologists in combination with clinical guidelines and practical experience, which is not conducive to efficient general screening

Method used

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  • Method for constructing AI chronic kidney disease screening model and chronic kidney disease screening method and system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0085] Such as figure 1 Shown, a kind of AI chronic kidney disease screening method, comprises the following steps:

[0086] Step S1, establishing an effective chronic kidney disease screening model;

[0087] Step S2, sorting out user data to be screened;

[0088] Step S3, substituting the data of the user to be screened into the chronic kidney disease screening model for model calculation, and finally obtaining the result of kidney disease risk prediction.

[0089] Establishing an effective CKD screening model includes the following steps:

[0090] Step S11: Prepare medical record data; collect electronic medical records of patients from the hospital electronic medical record platform, and collect electronic medical records of chronic kidney disease patients and non-chronic kidney disease patients;

[0091] The method for collecting electronic medical records of patients with chronic kidney disease as a result of the diagnosis is as follows: comparing the diagnosis results...

Embodiment 2

[0144] The present invention also proposes a method for building an AI chronic kidney disease screening model, comprising the steps of:

[0145] Using the sklearn package of the python development language, three models of BP neural network, XGBoost and random forest were used to establish an integrated learning classifier system; a suitable chronic kidney disease screening parameter set that can distinguish chronic kidney disease was established, and the BP neural network, XGBoost The data is trained and iteratively trained with the three random forest models, and the chronic kidney disease screening parameter set is tuned to finally obtain a chronic kidney disease screening parameter set that can distinguish chronic kidney disease. The chronic kidney disease screening parameter set Including adaptive BP neural network neuron weights and biases that can distinguish chronic kidney disease, medical features and thresholds in random forest decision tree nodes, and medical feature...

Embodiment 3

[0164] Further, the present invention also proposes an AI chronic kidney disease screening system, including an effective screening model for chronic kidney disease, and the effective screening model for chronic kidney disease includes an integrated learning classification established by three models of BP neural network, XGBoost and random forest organ system, and an appropriate chronic kidney disease screening parameter set that can identify chronic kidney disease.

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Abstract

The invention provides a chronic kidney disease screening method and system, and particularly relates to a machine learning method for constructing a chronic kidney disease screening model, which comprises the steps of establishing an effective chronic kidney disease screening model, arranging user data to be screened, substituting the user data to be screened into the chronic kidney disease screening model for model calculation, and finally obtaining a kidney disease risk result. Therefore, the chronic kidney disease screening system is efficient, low in cost and high in accuracy. According to the method, a machine learning BP neural network, XGBoost and a random forest integration algorithm are adopted to train a chronic kidney disease screening model; high-risk groups with chronic kidney diseases can be automatically screened out according to basic body measurement information, symptom information, medical examination information, family history, past history, living habits and other data, and the accuracy reaches up to 0.96 or above.

Description

technical field [0001] The present invention relates to a chronic kidney disease screening method and system, in particular to a machine learning method to construct a chronic kidney disease screening model, a chronic kidney disease screening evaluation method and system, using the model, evaluation method and system to evaluate the medical characteristics of physical examination personnel Screening is carried out, and the risk assessment value of chronic kidney disease is given, so as to achieve high-efficiency, low-cost, and high-accuracy screening of chronic kidney disease. Background technique [0002] Chronic kidney disease has the characteristics of high prevalence, low awareness rate, poor prognosis and high medical expenses. It is another disease that seriously endangers human health after cardiovascular and cerebrovascular diseases, diabetes and malignant tumors. In recent years, with the aging of my country's population, the incidence of diseases such as diabetes a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/30G16H50/20G06N3/08G06N20/20
CPCG06N3/084G16H50/20G16H50/30G06N20/20
Inventor 黎海源
Owner SHENTAIWANG HEALTHCARE TECH NANJING CO LTD
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