一组八个关键问题帮助分类常见前庭疾病——来自DizzyReg患者登记结果

包含1066例常见前庭疾病患者的八个关键变量,用于通过分类树进行疾病分类的表格数据集。

NIAID Data Ecosystem
浏览 11
表格vertigodiagnosismachine learningsurveys and questionnairesclinical decision-making
Table_1_A_Set_of_Eight_Key_Questions_Helps_to_Classify_Common_Vestibular_Disorders—Results_From_the_DizzyReg_Patient_Registry.DOCX

基本信息

模态
表格
大小
0.000680022 GB
许可
CC BY 4.0
创建/更新时间
2026-10-07
版本
v1

资源简介

一组八个关键问题帮助分类常见前庭疾病——来自DizzyReg患者登记结果

【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 680.02 KB,主题涵盖 vertigo、diagnosis、machine learning、surveys and questionnaires、clinical decision-making,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《Table_1_A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders—Results From the DizzyReg Patient Registry.DOCX》。源站首次发布:2021-04-29。

【数据内容】

源站原始描述:Precise history taking is the key to develop a first assumption on the diagnosis of vestibular disorders. Particularly in the primary care setting, algorithms are needed, which are based on a small number of questions and variables only to guide appropriate diagnostic decisions. The aim of this study is to identify a set of such key variables that can be used for preliminary classification of the most common vestibular disorders. A four-step approach was implemented to achieve this aim: (1) we c…

【数据结构与技术规格】

文件数 1 个,合计 680.02 KB。Table_1_A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders—Results From the DizzyReg Patient Registry.DOCX:application/vnd.openxmlformats-officedocument.wordprocessingml.document,680.02 KB。数据集 DOI:10.3389/fneur.2021.670944.s001。

【主题与分类】

源站学科分类:Neurology and Neuromuscular Diseases、Neurogenetics。主题标签:vertigo、diagnosis、machine learning、surveys and questionnaires、clinical decision-making。

【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://frontiersin.figshare.com/articles/dataset/Table_1_A_Set_of_Eight_Key_Questions_Helps_to_Classify_Common_Vestibular_Disorders_Results_From_the_DizzyReg_Patient_Registry_DOCX/14503650

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Strobl, Ralf; Grözinger, Michael; Zwergal, Andreas; Huppert, Doreen; Filippopulos, Filipp; Grill, Eva (2021). Table_1_A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders—Results From the DizzyReg Patient Registry.DOCX. Frontiers. Dataset

【使用注意】

· 源站最后修改于 2023-06-03,引用时请注意版本时效。

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

帮我联系

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)

命令行下载

curl -L -o "Table_1_A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders—Results From the DizzyReg Patient Registry.DOCX" "https://ndownloader.figshare.com/files/27788307"

文件清单

  • Table_1_A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders—Results From the DizzyReg Patient Registry.DOCX(680.02 KB)

文件总体积 680.02 KB(源站 API 实测)。

数据说明

Precise history taking is the key to develop a first assumption on the diagnosis of vestibular disorders. Particularly in the primary care setting, algorithms are needed, which are based on a small number of questions and variables only to guide appropriate diagnostic decisions. The aim of this study is to identify a set of such key variables that can be used for preliminary classification of the most common vestibular disorders. A four-step approach was implemented to achieve this aim: (1) we conducted an online expert survey to collect variables that are meaningful for medical history taking, (2) we used qualitative content analysis to structure these variables, (3) we identified matching variables of the patient registry of the German Center for Vertigo and Balance Disorders, and (4) we used classification trees to build a classification model based on these identified variables and to analyze if and how these variables contribute to the classification of common vestibular disorders. We included a total of 1,066 patients with seven common vestibular disorders (mean age of 51.1 years, SD = 15.3, 56% female). Functional dizziness was the most frequent diagnosis (32.5%), followed by vestibular migraine (20.2%) and Menière’'s disease (13.3%). Using classification trees, we identified eight key variables which can differentiate the seven vestibular disorders with an accuracy of almost 50%. The key questions comprised attack duration, rotational vertigo, hearing problems, turning in bed as a trigger, doing sport or heavy household chores as a trigger, age, having problems with walking in the dark, and vomiting. The presented algorithm showed a high-face validity and can be helpful for taking initial medical history in patients with vertigo and dizziness. Further research is required to evaluate if the identified algorithm can be applied in the primary care setting and to evaluate its external validity.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fneur.2021.670944.s001(source: https://frontiersin.figshare.com/articles/dataset/Table_1_A_Set_of_Eight_Key_Questions_Helps_to_Classify_Common_Vestibular_Disorders_Results_From_the_DizzyReg_Patient_Registry_DOCX/14503650)。

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。

获取专属数据定制方案