Boosting algorithm-based construction method and construction system of Kawasaki disease risk assessment model

A technology of risk assessment model and construction method, which is applied in medical simulation, medical data mining, computer-aided medical procedures, etc., can solve problems such as delay in patient treatment and insufficient specificity, and achieve reduced detection costs, outstanding advantages, and detection short-term effect

Active Publication Date: 2019-01-25
DAOZHI PRECISION MEDICINE TECH SHANGHAI CO LTD
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  • Abstract
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AI Technical Summary

Problems solved by technology

Due to insufficient sensitivity and specificity, patients with Kawasaki disease are missed and misdiagnosed, thus delaying the treatment of patients

Method used

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  • Boosting algorithm-based construction method and construction system of Kawasaki disease risk assessment model
  • Boosting algorithm-based construction method and construction system of Kawasaki disease risk assessment model
  • Boosting algorithm-based construction method and construction system of Kawasaki disease risk assessment model

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Experimental program
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Effect test

Embodiment 1

[0109] In order to verify the effectiveness of a system for constructing a Kawasaki disease risk assessment model based on the Boosting algorithm of the present invention, this example selects 42,498 patient data in the electronic case from July 2008 to March 2018. This embodiment adopts the xgboosting method.

[0110] 1. Data processing:

[0111]After the original data set is deleted, the incomplete data set includes 8204 samples, and the complete data set contains 471 samples. According to the present invention, the data set has the form: each row represents information of a patient, and each column represents a characteristic information, such as ID, group, gender, age, CRP, FG, etc., and the format of the data set is as Table 1.

[0112] Through data sample selection and feature screening, the final generated data set contains 8675 rows and 11 columns of features, as shown in Table 1.

[0113] Table 1

[0114]

[0115] 2. Optimal model data

[0116] The incomplete d...

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Abstract

The invention discloses a boosting algorithm-based construction method and construction system of a Kawasaki disease risk assessment model. The construction method includes the following steps that: valid samples that can be used for modeling assessment are extracted from a sample data set; 10 features that meet on-site medical auxiliary diagnosis application are selected from the feature set of the valid sample; the incomplete data set of the valid samples is randomly divided into a training set and a verification set; a boosting method is adopted to fit the training set, so as to perform model construction, and a ten-fold cross-validation method is adopted to record optimal model parameters; and the verification set is adopted to calculate a model classification threshold t according toan ROC curve, and therefore, the Kawasaki disease risk assessment model is constructed. The invention also provides a corresponding Kawasaki disease risk assessment system for assessing data to be assessed so as to obtain a KDx score. With the system and method of the invention adopted, the rate of misdiagnosis and the rate of missed diagnosis of the Kawasaki disease can be decreased, and patientscan obtain effective prevention, intervention and treatment in the early stage of the disease.

Description

technical field [0001] The invention relates to a method for constructing a model, in particular to a method for constructing an assessment model for predicting Kawasaki disease risk based on a Boosting algorithm, a construction system, and an assessment system, belonging to the technical field of risk assessment model construction. technical background [0002] Kawasaki disease, also known as Pediatric Mucocutaneous Lymph Node Syndrome, is an acute febrile and eruptive disease with systemic vasculitis as the main lesion. disease draws people's attention. The most common symptom of Kawasaki disease is persistent fever. Its clinical manifestations are similar to those of common diseases such as pneumonia. It is easy to cause missed or misdiagnosed diseases, which may leave coronary artery damage and even threaten life. It is the most common cause of acquired heart disease in children, and it is also Risk factors for hemorrhagic heart disease. The timing of treatment of Kawa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/50G16H50/70G16H50/20
CPCG16H50/20G16H50/50G16H50/70
Inventor 丁国徽贾佳李光徐重飞周珍
Owner DAOZHI PRECISION MEDICINE TECH SHANGHAI CO LTD
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