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Kawasaki disease classifying and predicting method based on medical data modeling

A prediction method and technology of medical data, applied in the field of medical prediction, can solve problems such as ineffective use of nonlinear factors, achieve the effect of reducing misdiagnosis rate and improving treatment process

Pending Publication Date: 2017-01-04
QINGDAO UNIV
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AI Technical Summary

Problems solved by technology

[0004] The model constructed by the linear method is simple, and the results are easy to be understood by doctors, but it cannot effectively use the nonlinear factors of the characteristics of the data samples to improve the performance and accuracy of the model

Method used

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  • Kawasaki disease classifying and predicting method based on medical data modeling
  • Kawasaki disease classifying and predicting method based on medical data modeling
  • Kawasaki disease classifying and predicting method based on medical data modeling

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Experimental program
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Effect test

Embodiment 1

[0065] In order to verify the effectiveness of a Kawasaki disease classification prediction method based on medical data modeling of the present invention, this embodiment selects 894 patient data in the electronic medical records from November 2005 to June 2013.

[0066] 1. Data processing:

[0067] According to the present invention, the data set has the form: each row represents information of a patient, and each column represents one aspect of information, such as ID, physical examination information, Kawasaki disease category, etc., and the format of the data set is as Table 1. The original data set contains 918 patient data, 19 features, 36 duplicate data records were removed from the data set, and finally 882 patient data remained.

[0068] Through data sample selection and feature screening, the final generated data set contains 882 rows and 19 columns of features, as shown in Table 1.

[0069]

[0070] Table 1

[0071] 2. Optimal model parameters

[0072] The da...

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Abstract

The invention provides a kawasaki disease classifying and predicting method based on medical data modeling. The method includes the following steps of firstly, selecting data samples, and extracting an effective sample for modeling from a sample data set; secondly, screening characteristics, and screening out 19 characteristics meeting on-site medical assistance diagnosis application from a characteristic set for establishing sample data for modeling; thirdly, establishing and evaluating a kawasaki disease classifying model. The method is used for systematical analyzing and modeling of kawasaki disease related data and giving model prediction; by means of the mode, effective assistance diagnosis can be conducted on the kawasaki disease of a patient based on the kawasaki disease data, effective prevention, interference and treatment are conducted in the early period of disease attack, and a basis is provided for the optimal treatment effect.

Description

technical field [0001] The invention relates to the technical field of medical prediction, in particular to a Kawasaki disease grading prediction method based on medical data modeling. Background technique [0002] Kawasaki disease (KD) is an acute, self-limiting acute inflammatory vasculitis of unknown etiology, and has become the most common acquired heart disease in infants and young children. Failure to promptly diagnose and treat infants with Kawasaki disease with intravenous immune globulin (IVIG) can lead to dilated coronary arteries or aneurysms. The pathogenesis of Kawasaki disease is currently unknown, there is no effective diagnostic test, and it can easily be misdiagnosed as common fever. In addition, misdiagnosis of children with Kawasaki disease with cardiovascular sequelae may lead to myocardial infarction and death in 25% of cases. [0003] The Kawasaki disease classification prediction model based on medical data modeling can assist diagnosis, help reduce ...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 纪俊喻海清于滨
Owner QINGDAO UNIV
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