Resources


Model Credentialed Access

RadVLM model

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, Moritz Vandenhirtz, Sonia Laguna, Alain Ryser, Koji Fujimoto, Mizuho Nishio, Thomas Sutter, Julia Vogt, Jonas Kluckert, Thomas Frauenfelder, Christian Bluethgen, Farhad Nooralahzadeh, Michael Krauthammer

RadVLM is a 7B-parameter vision-language model fine-tuned on public chest-X-ray data that drafts reports, lists abnormalities, grounds findings, and chats about a CXR through a single image-to-text interface.

Published: Oct. 8, 2025. 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

RadGraph-XL is a large, expert-annotated dataset of 2,300 radiology reports covering multiple modalities and anatomies. It enables accurate extraction of clinical entities and relations for downstream medical AI tasks.

Published: Sept. 12, 2025. Version: 1.0.0

Database Open Access

CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images

Nicolas Gaggion, Candelaria Mosquera, Martina Aineseder, Lucas Mansilla, Diego Milone, Enzo Ferrante

CheXmask Database is a 657,566 uniformly annotated chest radiographs with segmentation masks. Images were segmented using HybridGNet, with automatic quality control indicated by RCA scores.

automatic quality assesment chest x-ray segmentation medical image segmentation

Published: Jan. 22, 2025. Version: 1.0.0

Database Credentialed Access

RadCoref: Fine-tuning coreference resolution for different styles of clinical narratives

Yuxiang Liao, Hantao Liu, Irena Spasic

RadCoref is a small subset of MIMIC-CXR with manually annotated coreference mentions and clusters. Based on the annotated data, we fine-tuned a deep neural model and used it to annotate the whole MIMIC-CXR dataset. Both data are available.

natural language processing coreference resolution radiology

Published: Jan. 30, 2024. Version: 1.0.0

Database Credentialed Access

CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-rays

Hyungyung Lee, Geon Choi, Jung Oh Lee, Hangyul Yoon, Hyuk Gi Hong, Edward Choi

CheXStruct is an automated pipeline that derives structured diagnostic reasoning steps from chest X-rays. CXReasonBench builds on this to evaluate whether models perform clinically grounded, multi-step reasoning beyond final diagnoses.

evaluation chest x-ray benchmark structured chest x-ray qa intermediate reasoning steps structured reasoning grounded reasoning diagnostic reasoning structured diagnostic pipeline

Published: Oct. 23, 2025. Version: 1.0.1

Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, Moritz Vandenhirtz, Sonia Laguna, Alain Ryser, Koji Fujimoto, Mizuho Nishio, Thomas Sutter, Julia Vogt, Jonas Kluckert, Thomas Frauenfelder, Christian Bluethgen, Farhad Nooralahzadeh, Michael Krauthammer

This dataset is designed to construct RadVLM, a vision–language model for chest X-ray interpretation. It includes instruction data for tasks such as report generation, abnormality detection, and region grounding, and multitask conversation.

chest x-rays vision-language models medical ai

Published: Sept. 25, 2025. Version: 1.0.0

Database Credentialed Access

Medical-Diff-VQA: A Large-Scale Medical Dataset for Difference Visual Question Answering on Chest X-Ray Images

Xinyue Hu, Lin Gu, Qiyuan An, Mengliang Zhang, liangchen liu, Kazuma Kobayashi, Tatsuya Harada, Ronald Summers, Yingying Zhu

MIMIC-Diff-VQA provides a large-scale dataset for Difference visual question answering in medical chest x-ray images.

difference visual question answering difference vqa vqa chest x-ray visual question answering

Published: Feb. 3, 2025. Version: 1.0.1

Database Credentialed Access

RadGraph2: Tracking Findings Over Time in Radiology Reports

Adam Dejl, Sameer Khanna, Patricia Therese Pile, Kibo Yoon, Steven QH Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar

RadGraph2 is a dataset of 800 chest radiology reports annotated using a fine-grained entity-relationship schema, which captures key findings as well as mentions of changes that occurred in comparison with the previous radiology studies.

chest x-rays relation extraction disease progression information extraction radiology reports named entity recognition

Published: Aug. 8, 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, 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 machine learning evaluation chest x-ray multi-modal question answering ehr question answering semantic parsing benchmark electronic health records deep learning visual question answering

Published: July 23, 2024. Version: 1.0.0

Database Credentialed Access

Radiology Report Expert Evaluation (ReXVal) Dataset

Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Lee, Zahra Shakeri, Andrew Ng, Curtis Langlotz, Vasantha Kumar Venugopal, Pranav Rajpurkar

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports.

Published: June 20, 2023. Version: 1.0.0