Published on 01 January 2025

Interpretable Web-Based Machine Learning Model for IVIG Resistance in Kawasaki Disease

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He, Ying;Huang, Hongbiao

Description

Data ContentThis dataset includes comprehensive clinical and laboratory data from pediatric KD patients admitted to Fujian Provincial Hospital, affiliated with Fuzhou University. The data were collected retrospectively and include demographic characteristics, laboratory test results, and treatment details.UsageThis dataset is valuable for researchers and clinicians working on:Developing predictive models for IVIG resistance in KD.Exploring biomarkers associated with treatment response.Conducting comparative studies on pediatric vasculitis.Enhancing personalized treatment strategies for KD patients.Ethical ConsiderationsThe dataset has been fully anonymized to ensure patient confidentiality. Data collection and handling were conducted in compliance with ethical standards. The study was approved by the institutional ethics committee, and all procedures followed ethical guidelines for medical research involving human subjects.

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Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

13%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

Assigned Domain

Subfield

Public Health, Environmental and Occupational Health

Field

Medicine

Domain

Health Sciences

Confidence Score

61%

Source

Scholar Data Model

Keywords

Paediatrics not elsewhere classified

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00