川崎病IVIG耐药性可解释网页机器学习模型数据集
川崎病患儿的临床与实验室数据，用于构建可解释网页机器学习模型以预测IVIG耐药性。
基本信息
资源简介
川崎病IVIG耐药性可解释网页机器学习模型数据集
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集，收录 1 个文件、合计 81.59 KB，主题涵盖 Kawasaki disease、IVIG resistance、Clinical dataset，可用于统计建模、特征工程与队列分析，CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Interpretable Web-Based Machine Learning Model for IVIG Resistance in Kawasaki Disease》。项目资助方：This work was supported by the Program for the Middle-aged and Young Key Talents in the Health System of Fujian Province [grant number 2024GGA010] and Fujian Provincial Natural Science Foundation [Grant number 2023J011211].。源站首次发布：2025-03-01。
【数据内容】
源站原始描述：Data Content This 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. Usage This dataset is valuable for researchers and clinicians working on: - Developing predictive models for IVIG resistance in KD. - Exploring biomarkers associated with treatment response.…
主表 fzdata.csv 含 42 列、样本前 464 行结构完整。
【数据结构与技术规格】
文件数 1 个，合计 81.59 KB。fzdata.csv：text/csv，81.59 KB。数据集 DOI：10.6084/m9.figshare.28516721.v1。
【主题与分类】
源站学科分类：Paediatrics not elsewhere classified。主题标签：Kawasaki disease、IVIG resistance、Clinical dataset。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://figshare.com/articles/dataset/Interpretable_Web-Based_Machine_Learning_Model_for_IVIG_Resistance_in_Kawasaki_Disease/28516721
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：He, Ying; Huang, Hongbiao (2025). Interpretable Web-Based Machine Learning Model for IVIG Resistance in Kawasaki Disease. figshare. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载，适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档，适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务（收技术服务费，非数据销售）
暂未开放当前数据集主要来源为 Kaggle 公开托管，完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取（Figshare）
- 源站标题：Interpretable Web-Based Machine Learning Model for IVIG Resistance in Kawasaki Disease
- DOI：10.6084/m9.figshare.28516721.v1
- 发布日期：2025-03-01
- 文件数：1 个
- 文件总体积：81.59 KB
- 源站页面：https://figshare.com/articles/dataset/Interpretable_Web-Based_Machine_Learning_Model_for_IVIG_Resistance_in_Kawasaki_Disease/28516721
命令行下载
curl -L -o "fzdata.csv" "https://ndownloader.figshare.com/files/52704458"
文件清单
fzdata.csv（81.59 KB）
文件总体积 81.59 KB（源站 API 实测）。
数据说明
Data Content
This 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.
Usage
This 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 Considerations
The 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.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.28516721.v1（source: https://figshare.com/articles/dataset/Interpretable_Web-Based_Machine_Learning_Model_for_IVIG_Resistance_in_Kawasaki_Disease/28516721）。
数据缺失？
依托陕西、四川两大基地，我们与超过十家三甲医院建立直接合作关系，覆盖合规授权、采集治理、专业标注、数据交付的全流程，为AI医疗团队提供即拿即用的高质量临床数据。
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