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Construction method and construction system for Kawasaki disease risk assessment model based on neural network algorithm

A technology of risk assessment model and neural network algorithm, which is applied in the field of assessment system and model construction, can solve the problems of delay in patient treatment and lack of specificity, and achieve the effect of reducing the cost of detection, highlighting advantages, and preventing delay in patient treatment

Active Publication Date: 2019-01-18
DAOZHI PRECISION MEDICINE TECH SHANGHAI CO LTD
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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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  • Construction method and construction system for Kawasaki disease risk assessment model based on neural network algorithm
  • Construction method and construction system for Kawasaki disease risk assessment model based on neural network algorithm
  • Construction method and construction system for Kawasaki disease risk assessment model based on neural network algorithm

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Embodiment 1

[0114] In order to verify the effectiveness of the construction system of the Kawasaki disease risk assessment model based on the neural network algorithm of the present invention, this embodiment selects 42,498 patient data in the electronic case from July 2008 to March 2018. This embodiment adopts the neural network method.

[0115] 1. Data processing:

[0116] 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.

[0117] 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.

[0118] Table 1

[0119]

[0120] 2. Optimal model data

[0121]...

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Abstract

The invention discloses a construction method and a construction system for a Kawasaki disease risk assessment model based on a neural network algorithm. The construction method comprises the steps: extracting valid samples which can be used for modeling and assessment from a sample data set; selecting ten features meeting field medical auxiliary diagnostic application from the feature set of thevalid samples; randomly dividing the incomplete data set of the valid samples into a training set and a validation set; fitting the training set by using the neural network method to construct the model and recording the optimal model parameters by using the ten-fold cross-validation method; and calculating the model classification threshold t by using the validation set according to the ROC curveso as to construct the Kawasaki disease risk assessment model. The corresponding Kawasaki disease risk assessment system is also constructed to be applied to assessment of the data to be assessed soas to obtain the KDx score. The misdiagnosis rate and the missed diagnosis rate of the Kawasaki disease can be reduced so that the patients can obtain effective prevention, intervention and treatmentin 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 neural network 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 mucocutaneous lymph node syndrome, is an autoimmune disease with systemic vasculitis as the main lesion, and has affected more than 60 countries around the world. Among them, the coronary artery is more likely to be involved, and it is a febrile eruptive disease of unknown cause. Kawasaki disease mainly manifests as persistent fever for more than 5 days, and also includes: (1) Symptoms of conjunctival congestion in both eyes, but no exudation (2) redness of the lips, red bayberry tongue, and diffuse congestion of the oral and pharyngeal mucosa; (3) erythema multiforme and rash on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/20G16H50/30
CPCG16H50/20G16H50/30
Inventor 丁国徽黄敏张泓王淑蒋蓓贾佳李光徐重飞周珍
Owner DAOZHI PRECISION MEDICINE TECH SHANGHAI CO LTD
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