A method and system for constructing a Kawasaki disease risk assessment model based on boosting algorithm

A technology for risk assessment models and construction methods, applied in medical simulation, medical data mining, computer-aided medical procedures, etc., can solve the problems of delayed patient treatment, lack of specificity, etc. The effect of delaying patient treatment conditions

Active Publication Date: 2021-11-12
DAOZHI PRECISION MEDICINE TECH SHANGHAI CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method and system for constructing a Kawasaki disease risk assessment model based on boosting algorithm
  • A method and system for constructing a Kawasaki disease risk assessment model based on boosting algorithm
  • A method and system for constructing a Kawasaki disease risk assessment model based on boosting algorithm

Examples

Experimental program
Comparison scheme
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...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a method and system for constructing a Kawasaki disease risk assessment model based on a Boosting algorithm. The construction method includes: extracting effective samples that can be used for modeling evaluation from the sample data set; screening out 10 features that meet the application of on-site medical auxiliary diagnosis from the feature set of the effective samples; randomly dividing the incomplete data set of the effective samples It is the training set and the verification set; use the Boosting method to fit the training set to build the model, and use the ten-fold cross-validation method to record the optimal model parameters; use the verification set to calculate the model classification threshold t according to the ROC curve, so as to construct the risk of Kawasaki disease Evaluate the model. The present invention also constructs a corresponding Kawasaki disease risk assessment system and applies it to assess the data to be assessed to obtain a KDx score. The invention helps to reduce the rate of misdiagnosis and missed diagnosis of Kawasaki disease, so that patients can obtain effective prevention, intervention and treatment in the early stage of onset.

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. Background technique [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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap