Resources

54 results for "large language model"

Database Credentialed Access

MIMIC-Ext-SynNotes: Large-Scale Synthetic Clinical Notes via Rephrasing MIMIC-III/IV with LLMs

Jinghui Liu, Sarvesh Soni, Anthony Nguyen

MIMIC-III and MIMIC-IV are foundational resources for clinical NLP, but their scale is modest relative to the data volumes needed to train language models. Building on recent advances in synthetic data generation through LLM-based rephrasing, we con…
Published: Oct. 5, 2026. Version: 1.0
Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, et al.

We release a new dataset, MS-CXR, with locally-aligned phrase grounding annotations by board-certified radiologists to facilitate the study of complex semantic modelling in biomedical vision–language processing. The MS-CXR dataset provides 1162 imag…
Published: Nov. 15, 2024. Version: 1.1.0
Model Credentialed Access

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

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

Veterinary medical records represent a large data resource for application to veterinary and One Health clinical research efforts. Use of the data is limited by interoperability challenges including inconsistent data formats and data siloing. Clinic…
Published: Jan. 25, 2026. Version: 1.0.0
Database Credentialed Access

MIMIC-IV-Note: Deidentified free-text clinical notes

Alistair Johnson, Tom Pollard, Steven Horng, et al.

The advent of large, open access text databases has driven advances in state-of-the-art model performance in natural language processing (NLP). The relatively limited amount of clinical data available for NLP has been cited as a significant barrier …
Published: Jan. 6, 2023. Version: 2.2
Database Credentialed Access

MedVAL-Bench: Expert-Annotated Medical Text Validation Benchmark

Asad Aali, Vasiliki Bikia, Maya Varma, et al.

MedVAL-Bench is a dataset containing physician evaluations of errors in language model (LM)-generated medical text. The dataset spans 6 diverse medical text generation tasks and includes annotations from 12 physicians on clinically significant error…
Published: Nov. 14, 2025. Version: 1.0.1
Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

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

We introduce MIMIC-Ext-MIMIC-CXR-VQA (i.e., Extended from MIMIC database), a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs. This datase…
Published: July 19, 2024. Version: 1.0.0
Database Credentialed Access

RadGraph-XL: A Large-Scale Expert-Annotated Dataset for Entity and Relation Extraction from Radiology Reports

Jean-Benoit Delbrouck

Radiology reports are essential for clinical care but pose challenges for automated processing due to their unstructured nature. Existing datasets like RadGraph-1.0 focus narrowly on chest X-rays (CXR), limiting their applicability. We introduce Rad…
Published: Sept. 12, 2025. Version: 1.0.0
Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

We release the RadVLM instruction dataset, a large-scale resource used to train the RadVLM model on diverse radiology tasks. The dataset contains 1,115,021 image–instruction pairs spanning five task families: (i) report generation from frontal CXRs …
Published: Sept. 25, 2025. Version: 1.0.0
Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, et al.

In recent years, with the release of multiple large datasets, automatic interpretation of chest X-ray (CXR) images with deep learning models have become feasible for specific abnormalities or for generating preliminary reports. However, despite repo…
Published: July 13, 2021. Version: 1.0.0
Database Credentialed Access

BRAX, a Brazilian labeled chest X-ray dataset

Eduardo Pontes Reis, Joselisa Paiva, Maria Carolina Bueno da Silva, et al.

The Brazilian labeled chest x-ray dataset (BRAX) is an automatically labeled dataset designed to assist researchers in the validation of machine learning models. The dataset contains 24,959 chest radiography studies from patients presenting to a lar…
Published: June 17, 2022. Version: 1.1.0