官方服务：
资源简介：
All patients data without names
应用场景：
创建时间：
2018-06-30
相关数据集
EHRCon
EHRCon是由韩国科学技术院和三星医疗中心合作开发的数据集，旨在检查电子健康记录中非结构化笔记与结构化表格之间的一致性。该数据集包含3,943个实体，覆盖105份临床笔记，通过与MIMIC-III数据库中的数据进行对比标注。EHRCon提供两种版本，分别基于MIMIC-III和OMOP CDM架构，以增强通用性和适用性。数据集主要用于解决医疗记录中数据不一致的问题，确保患者安全，避免医疗错误。
arXiv2024-06-24 更新230
External validation of an electronic health record-based diagnostic model for histological acute tubulointerstitial nephritis
Background Accurate diagnosis of acute tubulointerstitial nephritis (AIN) often requires a kidney biopsy. We previously developed a diagnostic statistical model for predicting biopsy-confirmed AIN by
DataONE2024-12-12 更新110
Improved_Descriptive_Statistics.docx
This study investigated factors influencing nurses' use of electronic health record (EHR) systems in resource-limited settings in Botswana, and the authors propose strategies for improved adoption and
DataCite Commons2024-10-03 更新230
Daily Count Data for International Electronic Health Record-Derived COVID-19 Clinical Course Profile: The 4CE Consortium
Data for all daily count figures in the 4CE manuscript "International Electronic Health Record-Derived COVID-19 Clinical Course Profile: The 4CE Consortium" (Preprint: https://doi.org/10.1101/2020.04.
NIAID Data Ecosystem120
