多发性硬化症患者电子健康记录衍生队列特征数据集
基于电子健康记录的多发性硬化症患者队列特征数据,包含人口统计、诊断及治疗信息。

基本信息
资源简介
多发性硬化症患者电子健康记录衍生队列特征数据集
【数据集背景】
本数据集源站标题为《Characteristics of the EHR-derived cohort of multiple sclerosis (MS) patients and the subset of patients who receive care at a subspecialty MS Centera.》,为 the EHR-derived cohort of multiple sclerosis (MS) patients and the subset of patients who receive care at a subspecialty MS Centera. 的组成部分。配套论文《Modeling Disease Severity in Multiple Sclerosis Using Electronic Health Records》发表于 PLoS ONE(2013),DOI:10.1371/journal.pone.0078927。源站首次发布:2013-11-11。
【数据内容】
源站原始描述:aA subset of the patients in the EHR-derived MS cohort receives neurological care at the Partners MS Center where neuroimaging and clinical outcomes are available. For comparison, our cohort shares similar basic demographic characteristics as an independent MS patient registry from the North American Research Committee on Multiple Sclerosis (NARCOMS): 73% of the NARCOMS patients are female, 90% are self-described White, mean age at diagnosis is 37 years, and 52% of the patients are receiving imm…
【数据结构与技术规格】
文件数 1 个,合计 9.73 KB。Table_2.xls:application/vnd.ms-excel,9.73 KB。数据集 DOI:10.1371/journal.pone.0078927.t002。
【主题与分类】
源站学科分类:Biological Sciences。主题标签:ehr-derived、cohort、sclerosis、patients、subset、subspecialty、ms。
【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/_Characteristics_of_the_EHR_derived_cohort_of_multiple_sclerosis_MS_patients_and_the_subset_of_patients_who_receive_care_at_a_subspecialty_MS_Center_a_/845949
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Xia, Zongqi; Secor, Elizabeth; B. Chibnik, Lori; M. Bove, Riley; Cheng, Suchun; Chitnis, Tanuja; et al. (2015). Characteristics of the EHR-derived cohort of multiple sclerosis (MS) patients and the subset of patients who receive care at a subspecialty MS Centera.. PLOS ONE. 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。
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:Characteristics of the EHR-derived cohort of multiple sclerosis (MS) patients and the subset of patients who receive care at a subspecialty MS Center<sup>a</sup>.
- DOI:10.1371/journal.pone.0078927.t002
- 发布日期:2013-11-11
- 文件数:1 个
- 文件总体积:9.73 KB
- 源站页面:https://plos.figshare.com/articles/dataset/_Characteristics_of_the_EHR_derived_cohort_of_multiple_sclerosis_MS_patients_and_the_subset_of_patients_who_receive_care_at_a_subspecialty_MS_Center_a_/845949
命令行下载
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/1274883"
文件清单
Table_2.xls(9.73 KB)
文件总体积 9.73 KB(源站 API 实测)。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
aA subset of the patients in the EHR-derived MS cohort receives neurological care at the Partners MS Center where neuroimaging and clinical outcomes are available. For comparison, our cohort shares similar basic demographic characteristics as an independent MS patient registry from the North American Research Committee on Multiple Sclerosis (NARCOMS): 73% of the NARCOMS patients are female, 90% are self-described White, mean age at diagnosis is 37 years, and 52% of the patients are receiving immune modulatory therapy [32].
Abbreviation: ICD-9 = 340 is the diagnostic code for MS.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0078927.t002(source: https://plos.figshare.com/articles/dataset/_Characteristics_of_the_EHR_derived_cohort_of_multiple_sclerosis_MS_patients_and_the_subset_of_patients_who_receive_care_at_a_subspecialty_MS_Center_a_/845949)。
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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