Resources


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.

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

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

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

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

Published: March 19, 2025. Version: 1.0.1

Model Credentialed Access

Fine-tuning foundational models to code diagnoses from veterinary health records

Adam Kiehl, Nadia Saklou, G Joseph Strecker, et al.

Fine-tuned GatorTron LLM for veterinary diagnosis coding to 7,739 SNOMED-CT codes based on clinical summary text from the Colorado State University Veterinary Teaching Hospital.

transformers natural language processing large language models foundational models one health diagnoses snomed-ct veterinary medicine omop cdm veterinary medical records clinical coding

Published: Jan. 25, 2026. Version: 1.0.0

Model Credentialed Access

Fine-tuning foundational models to code diagnoses from veterinary health records

Adam Kiehl, Nadia Saklou, G Joseph Strecker, et al.

Fine-tuned GatorTron LLM for veterinary diagnosis coding to 7,739 SNOMED-CT codes based on clinical summary text from the Colorado State University Veterinary Teaching Hospital.

transformers natural language processing large language models foundational models one health diagnoses snomed-ct veterinary medicine omop cdm veterinary medical records clinical coding

Published: Jan. 25, 2026. 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.

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

Published: July 23, 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.

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

Published: July 23, 2024. 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.

The DFCI-imaging-student and DFCI-medonc-student AI models for extracting cancer outcomes from imaging reports and medical oncologist notes from electronic health records.

Published: Oct. 24, 2024. Version: 1.0.0

Database Credentialed Access

AIPatient KG: MIMIC-III and CORAL Electronic Health Records based Patient Knowledge Graph

Lizhou Fan, Huizi Yu

This project integrates MIMIC-III and CORAL electronic health records into knowledge graphs to improve medical analysis and enhance decision-making capabilities. Resources include two knowledge graph snapshots and two question-and-answering datasets.

Published: April 15, 2025. Version: 1.0.0

Database Contributor Review

CARMEN-I: A resource of anonymized electronic health records in Spanish and Catalan for training and testing NLP tools

Eulalia Farre Maduell, Salvador Lima-Lopez, Santiago Andres Frid, et al.

CARMEN-I is a Spanish corpus of 2,000 clinical records from Hospital Clínic, Barcelona. It covers COVID-19 patients and comorbidities, serving as a resource for training clinical NLP models and researchers in NLP applied to clinical documents.

de-identification clinical ner anonymization

Published: April 20, 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.

A clinician-labeled dataset for fact-checking long-form clinical text against patient EHRs. The dataset contains LLM-written and human-written Brief Hospital Course summaries decomposed to atomic claim and sentence propositions with annotations.

artificial intelligence natural language processing clinical notes electronic health records brief hospital course large language models long-form text chart review text reranking atomic claim hybrid retrieval clinical informatics clinical medicine fact verification retrieval-augmented generation logical atomism text embedding formal logic llm-as-a-judge llm evaluation

Published: April 9, 2025. Version: 1.0.0