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A method and system for constructing a Kawasaki disease risk assessment model based on a 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 problems such as delay in patient treatment and lack of specificity, and achieve the effects of reducing the cost of detection, highlighting advantages, and shortening the time used for diagnosis

Active Publication Date: 2021-11-12
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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  • A method and system for constructing a Kawasaki disease risk assessment model based on a neural network algorithm
  • A method and system for constructing a Kawasaki disease risk assessment model based on a neural network algorithm
  • A method and system for constructing a Kawasaki disease risk assessment model based on a neural network algorithm

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Embodiment 1

[0114] In order to verify the validity of the construction system of the Kawasaki disease risk assessment model based on the neural network algorithm of the present invention, the data of 42498 patients in the electronic case in the time range of 2008.7-2018.3 are selected in this embodiment. This embodiment adopts the neural network method.

[0115] 1. Data processing:

[0116] After the original dataset is deleted, the incomplete dataset includes 8204 samples, and the complete dataset includes 471 samples. According to the present invention, the data set has the form: each row represents the information of a patient, and each column represents its characteristic information, such as ID, group, gender, age, CRP, FG, etc. The format of the data set is as shown in Table 1.

[0117] Through data sample selection and feature screening, the final data set contains 8675 rows and 11 columns of features, as shown in Table 1.

[0118] Table 1

[0119]

[0120] 2. Optimal model d...

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Abstract

The invention discloses a method and system for constructing a Kawasaki disease risk assessment model based on a neural network 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 neural network 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 Kawasaki disease Risk Assessment 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 neural network algorithm, a constructing system, and an assessment system, belonging to the technical field of risk assessment model construction. Background technique [0002] Kawasaki disease, also known as mucocutaneous lymph node syndrome, is an autoimmune disease with systemic vasculitis as the main lesion, which has affected more than 60 countries around the world. Among them, coronary artery is a more easily involved part, which is a febrile rash disease of unknown cause. Kawasaki disease is mainly characterized by persistent fever for more than 5 days, and also includes: (1) Conjunctival symptoms of hyperemia in both eyes, but no exudation (2) redness of the lips, appearance of bayberry tongue, and diffuse congestion symptoms in the oral and pharyngeal mucosa; (3) erythema mul...

Claims

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Application Information

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Patent Type & Authority Patents(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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