登革热早期诊断新分类器的敏感性和特异性
基于5729名发热儿童数据,评估登革热早期诊断分类器的敏感性和特异性。

基本信息
资源简介
登革热早期诊断新分类器的敏感性和特异性
【数据集背景】
本数据集源站标题为《Sensitivity and Specificity of a Novel Classifier for the Early Diagnosis of Dengue》。配套论文《Sensitivity and Specificity of a Novel Classifier for the Early Diagnosis of Dengue》发表于 PLOS Neglected Tropical Diseases(2015),DOI:10.1371/journal.pntd.0003638。源站首次发布:2015-04-02。
【数据内容】
源站原始描述:Background Dengue is the commonest arboviral disease of humans. An early and accurate diagnosis of dengue can support clinical management, surveillance and disease control and is central to achieving the World Health Organisation target of a 50% reduction in dengue case mortality by 2020. Methods 5729 children with fever of Results The EDC had a sensitivity of 74.8% (95%CI: 73.0-76.8%) and specificity of 76.3% (95%CI: 75.2-77.6%) for the diagnosis of dengue. As an adjunctive test alongside NS1 r…
【数据结构与技术规格】
文件数 10 个,合计 3.16 MB。S1_Fig.doc:application/msword,299.01 KB。S2_Fig.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,195.38 KB。S1_Table.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,104.65 KB。数据集 DOI:10.1371/journal.pntd.0003638。
【主题与分类】
源站学科分类:Biological Sciences。主题标签:Disease Control、NS 1、adjunctive test、arboviral disease、patient management、Dengue Classifier、World Health Organisation target、patient age、dengue cases、2020. Methods 5729 children。
【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。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/_Sensitivity_and_Specificity_of_a_Novel_Classifier_for_the_Early_Diagnosis_of_Dengue_/1366186
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Minh Tuan, Nguyen; Thi Nhan, Ho; Van Vinh Chau, Nguyen; Thanh Hung, Nguyen; Manh Tuan, Ha; Van Tram, Ta; et al. (2016). Sensitivity and Specificity of a Novel Classifier for the Early Diagnosis of Dengue. PLOS Neglected Tropical Diseases. Dataset
【使用注意】
· 源站最后修改于 2023-05-30,引用时请注意版本时效。
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:Sensitivity and Specificity of a Novel Classifier for the Early Diagnosis of Dengue
- DOI:10.1371/journal.pntd.0003638
- 发布日期:2015-04-02
- 文件数:10 个
- 文件总体积:3.16 MB
- 源站页面:https://plos.figshare.com/articles/dataset/_Sensitivity_and_Specificity_of_a_Novel_Classifier_for_the_Early_Diagnosis_of_Dengue_/1366186
命令行下载
curl -L -o "S1_Fig.doc" "https://ndownloader.figshare.com/files/2003711"
curl -L -o "S2_Fig.docx" "https://ndownloader.figshare.com/files/2003712"
curl -L -o "S1_Table.docx" "https://ndownloader.figshare.com/files/2003713"
curl -L -o "S2_Table.docx" "https://ndownloader.figshare.com/files/2003714"
curl -L -o "S3_Table.docx" "https://ndownloader.figshare.com/files/2003715"
curl -L -o "S4_Table.docx" "https://ndownloader.figshare.com/files/2003716"
curl -L -o "S5_Table.docx" "https://ndownloader.figshare.com/files/2003717"
curl -L -o "S1_Text.docx" "https://ndownloader.figshare.com/files/2003718"
文件清单
S1_Fig.doc(299.01 KB)S2_Fig.docx(195.38 KB)S1_Table.docx(104.65 KB)S2_Table.docx(60.08 KB)S3_Table.docx(64.62 KB)S4_Table.docx(83.31 KB)S5_Table.docx(71.91 KB)S1_Text.docx(87.02 KB)S1_Dataset.xls(2.14 MB)S1_Checklist.doc(48.64 KB)
文件总体积 3.16 MB(源站 API 实测)。
数据说明
Background
Dengue is the commonest arboviral disease of humans. An early and accurate diagnosis of dengue can support clinical management, surveillance and disease control and is central to achieving the World Health Organisation target of a 50% reduction in dengue case mortality by 2020.
Methods
5729 children with fever of Results
The EDC had a sensitivity of 74.8% (95%CI: 73.0-76.8%) and specificity of 76.3% (95%CI: 75.2-77.6%) for the diagnosis of dengue. As an adjunctive test alongside NS1 rapid testing, sensitivity of the composite test was 91.6% (95%CI: 90.4-92.9%).
Conclusions
We demonstrate that the early diagnosis of dengue can be enhanced beyond the current standard of care using a simple evidence-based algorithm. The results should support patient management and clinical trials of specific therapies.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pntd.0003638(source: https://plos.figshare.com/articles/dataset/_Sensitivity_and_Specificity_of_a_Novel_Classifier_for_the_Early_Diagnosis_of_Dengue_/1366186)。
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。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




