Resources

36 results for "ehr"

Database Credentialed Access

EHR-ReasonCon: Reasoning-Intensive Consistency Verification Between Clinical Notes and Structured Tables in Electronic Health Records

Yeonsu Kwon, Jiho Kim, JunSeong Choi, et al.

Electronic Health Records (EHRs) combine structured data, such as medications and laboratory measurements, with unstructured clinical notes describing patient conditions and clinical events. Although these two data types provide complementary inform…
Published: Sept. 15, 2026. Version: 1.0.0
Database Credentialed Access

MIMIC-IV-Ext-Instr: A Dataset of 450K+ EHR-Grounded Instruction-Following Examples

Zhenbang Wu, Anant Dadu, Mike Nalls, et al.

Large language models (LLMs) have shown impressive capabilities in solving a wide range of tasks based on human instructions. However, developing a conversational AI assistant for electronic health record (EHR) data remains challenging due to the la…
Published: Sept. 9, 2025. Version: 1.0.0
Database Credentialed Access

EHR-DS-QA: A Synthetic QA Dataset Derived from Medical Discharge Summaries for Enhanced Medical Information Retrieval Systems

Konstantin Kotschenreuther

This dataset was designed and created to enable advancements in healthcare-focused large language models, particularly in the context of retrieval-augmented clinical question-answering capabilities. Developed using a self-constructed pipeline based …
Published: Jan. 11, 2024. Version: 1.0.0
Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

Electronic Health Records (EHRs), which contain patients' medical histories in various multi-modal formats, often overlook the potential for joint reasoning across imaging and table modalities underexplored in current EHR Question Answering (QA) sys…
Published: July 23, 2024. Version: 1.0.0
Challenge Credentialed Access

ArchEHR-QA: A Dataset for Addressing Patient's Information Needs related to Clinical Course of Hospitalization

Sarvesh Soni, Dina Demner-Fushman

Patient’s unique information needs about their hospitalization can be addressed using clinical evidence from electronic health records (EHRs) and artificial intelligence (AI). However, robust datasets to assess the factuality and relevance of AI-gen…
Published: Oct. 5, 2026. Version: 1.4
Database Credentialed Access

EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records

Yeonsu Kwon, Jiho Kim, Gyubok Lee, et al.

Electronic Health Records (EHRs) are integral for storing comprehensive patient medical records, combining structured data (e.g., medications) with detailed clinical notes (e.g., physician notes). These elements are essential for straightforward dat…
Published: March 19, 2025. Version: 1.0.1
Database Credentialed Access

DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries

Jayetri Bardhan, Anthony Colas, Kirk Roberts, et al.

Electronic Health Records (EHR) contain patient records, stored in structured tables as well as unstructured clinical notes. The information in structured and unstructured EHR records is not strictly disjoint: information may be duplicated, contradi…
Published: April 12, 2022. Version: 1.0.0
Model Credentialed Access

Shareable Artificial Intelligence to Extract Cancer Outcomes from Electronic Health Records for Precision Oncology Research

Kenneth Kehl, Pavel Trukhanov, Christopher Fong, et al.

Databases that link molecular data to clinical outcomes can inform precision cancer research into novel prognostic and predictive biomarkers. However, outside of clinical trials, cancer outcomes are typically recorded only in text form within electr…
Published: Oct. 24, 2024. Version: 1.0.0
Database Credentialed Access

Annotation dataset of social determinants of health from MIMIC-III Clinical Care Database

Marco Guevara, Shan Chen, Spencer Thomas, et al.

Social determinants of health (SDoH) have an important impact on patient outcomes but are incompletely collected from the electronic health records (EHR). This study researched the ability of large language models to extract SDoH from free text in E…
Published: Jan. 24, 2024. Version: 1.0.1
Database Credentialed Access

MIMIC-III-Ext-VeriFact-BHC: Labeled Propositions From Brief Hospital Course Summaries for Long-form Clinical Text Evaluation

Philip Chung, Akshay Swaminathan, Alex Goodell, et al.

The VeriFact-BHC dataset is designed to verify the factuality of long-form text written about a patient against their own electronic health record. There is increasing interest in using large language models (LLMs) to generate clinical text in patie…
Published: Aug. 27, 2026. Version: 1.1.0