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Database Credentialed Access

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

Konstantin Kotschenreuther

Dataset consisting of question and answer pairs synthetically generated from medical discharge summaries, designed to facilitate the training and development of large language models specifically tailored for healthcare applications

mimic-iv clinical question-answering medical discharge summaries large language models

Published: Jan. 11, 2024. Version: 1.0.0

Challenge Credentialed Access

ArchEHR-QA: BioNLP at ACL 2025 Shared Task on Grounded Electronic Health Record Question Answering

Sarvesh Soni, Dina Demner-Fushman

A dataset for grounded question answering (QA) from electronic health records (EHRs).

electronic health record question answering clinicians patient portals

Published: April 11, 2025. Version: 1.2

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, Daisy Zhe Wang

DrugEHRQA is a QA dataset containing question-answers from MIMIC-III tables and discharge summaries.

question-answer qa

Published: April 12, 2022. Version: 1.0.0

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, Daisy Zhe Wang

DrugEHRQA is a QA dataset containing question-answers from MIMIC-III tables and discharge summaries.

question-answer qa

Published: April 12, 2022. Version: 1.0.0

Database Credentialed Access

Annotated Question-Answer Pairs for Clinical Notes in the MIMIC-III Database

Xiang Yue, Xinliang Frederick Zhang, Huan Sun

Annotated Question Answering Pairs for Clinical Notes in the MIMIC-III Database

clinical question answering clinical nlp clinical reading comprehension

Published: Jan. 15, 2021. 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, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering chest x-ray benchmark evaluation multi-modal question answering ehr question answering semantic parsing machine learning deep learning electronic health records visual question answering

Published: July 23, 2024. Version: 1.0.0

Database Open Access

Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management

Cécile Logé, Emily Ross, David Yaw Amoah Dadey, Saahil Jain, Adriel Saporta, Andrew Ng, Pranav Rajpurkar

Q-Pain, a medical QA dataset designed to enable the substitution of multiple different racial and gender "profiles" for patients and to evaluate whether bias is present when deciding whether to prescribe pain medication or not.

Published: June 11, 2021. Version: 1.0.0

Database Credentialed Access

EHRNoteQA: An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

Sunjun Kweon, Jiyoun Kim, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon, Kwang Hyun Kim, Jeewon Yang, Seunghyun Won, Edward Choi

An LLM Benchmark for Real-World Clinical Practice Using Discharge Summaries

Published: June 26, 2024. Version: 1.0.1

Database Credentialed Access

Learning to Ask Like a Physician: a Discharge Summary Clinical Questions (DiSCQ) Dataset

Eric Lehman

Dataset of questions asked by medical experts about patients. Medical experts will read a discharge summary line-by-line and (1) ask any question that they may have and (2) record what in the text "triggered" them to ask their question.

question generation question answering machine learning

Published: July 28, 2022. Version: 1.0