Resources


Challenge Credentialed Access

SNOMED CT Entity Linking Challenge

Will Hardman, Mark Banks, Rory Davidson, Donna Truran, Nindya Widita Ayuningtyas, Hoa Ngo, Alistair Johnson, Tom Pollard

272 discharge notes from the MIMIC-IV-Note dataset annotated with SNOMED CT concepts.

snomed entity linking clinical annotation

Published: July 22, 2025. Version: 1.1.0

Database Credentialed Access

FDTooth: Intraoral Photographs and Cone-Beam Computed Tomography Images for Fenestration and Dehiscence Detection

Yanqi Yang, Xiaomeng LI, Keyuan Liu, Marawan Elbatel

FDTooth is a dataset containing intraoral photographs and cone-beam computed tomography (CBCT) images with annotations for automated detection of fenestration and dehiscence in anterior teeth.

Published: May 5, 2025. Version: 1.0.0

Database Credentialed Access

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters

Amin Dada, Osman Alperen Koras, Marie Bauer, Amanda Butler, Kaleb Smith, Jens Kleesiek, Julian Friedrich

MeDiSumQA is a dataset of patient-oriented QA pairs from MIMIC-IV discharge summaries, designed to evaluate LLMs in generating safe, patient-friendly medical responses for clinical QA and healthcare communication.

Published: May 5, 2025. Version: 1.0.0

Database Open Access

Minute level step counts and physical activity data from the National Health and Nutrition Examination Survey (NHANES) 2011-2014

Lily Koffman, John Muschelli

Minute level step counts obtained from five step counting algorithms for raw accelerometry data, and minute level Activity Counts, MIMS, wear predictions, and wear flags for all participants who wore accelerometers in NHANES 2011-2014.

accelerometry physical activity steps nhanes

Published: May 5, 2025. Version: 1.0.1

Database Credentialed Access

Medical Expert Annotations of Unsupported Facts in Doctor-Written and LLM-Generated Patient Summaries

Stefan Hegselmann, Shannon Shen, Florian Gierse, Monica Agrawal, David Sontag, Xiaoyi Jiang

Annotations for unsupported facts in 100 original MIMIC patient summaries (discharge instructions) and hallucinations in 100 Large Language Model (LLM) generated patient summaries labeled by two medical experts.

Published: April 30, 2025. Version: 1.0.1

Challenge Credentialed Access

CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays

Gregory Holste, Mingquan Lin, Song Wang, Yiliang Zhou, Yishu Wei, Hao Chen, Atlas Wang, Yifan Peng

CXR-LT 2024 was a challenge for long-tailed, multi-label, and zero-shot thorax disease classification on chest X-rays, held at MICCAI 2024. This page contains long-tailed labels for 45 diseases from the CXR-LT 2024 and 2023 challenges.

disease classification artificial intelligence chest x-ray deep learning computer-aided diagnosis long-tailed learning cardiopulmonary disease zero-shot learning

Published: March 19, 2025. Version: 2.0.0

Database Credentialed Access

MedVH: Towards Systematic Evaluation of Hallucination for Large Vision Language Models in the Medical Context

Zishan Gu, Jiayuan Chen, Fenglin Liu, Changchang Yin, Ping Zhang

MedVH provides a visual hallucination evaluation benchmark for large language models in the medical context. It formulates tests using chest X-ray images, including multi-choice question answering and long-text generation tasks.

Published: March 11, 2025. Version: 1.0.0

Database Open Access

Synthetic Mention Corpora for Disease Entity Recognition and Normalization

Kuleen Sasse, John David Osborne

We present the Synthetic Mention Corpora for Disease Entity Recognition and Normalization, containing 128000 disease mentions from the UMLS disorder group, generated by an LLM. This corpus aims to improve these tasks in biomedical and clinical texts.

nlp machine learning named entity recognition data augmentation entity normalization

Published: Feb. 3, 2025. Version: 1.0.0

Database Restricted Access

CXRGraph: Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation

Yuxiang Liao, Hoisang Heung, Hantao Liu, Irena Spasic

CXRGraph is a structured radiology report dataset built upon RadGraph and tailored for the Automatic Radiology Report Generation task. It can identify more task-relevant information such as abnormalities and hallucinated prior references.

relation extraction information extraction natural language processing named entity recognition structured radiology report

Published: Feb. 3, 2025. Version: 1.0.0

Database Credentialed Access

FFA-IR: Towards an Explainable and Reliable Medical Report Generation Benchmark

Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Tengfei Liu, Cong Wang, xin chen, zhong liu, Caineng Pan, Mengke Li, yingfeng zheng, Yizhi Liu, Flora Salim, Karin Verspoor, Xiaodan Liang, Xiaojun Chang

Benchmark dataset for report generation based on fundus fluorescein angiography images and reports.

fundus fluorescein angiography medical report generation vision and language explainable and reliable evaluation

Published: Jan. 21, 2025. Version: 1.1.0