Resources

160 results for "mimic"

Challenge Credentialed Access

SNOMED CT Entity Linking Challenge

Will Hardman, Mark Banks, Rory Davidson, et al.

This challenge, sponsored by SNOMED International, seeks to advance the development of Entity Linking models that operate on unstructured clinical texts. Participants in the challenge will train entity linking models using a subset of MIMIC-IV-Note …
Published: Feb. 17, 2026. Version: 1.2.1
Database Credentialed Access

Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation

Jong Hak Moon, Geon Choi, Paloma Rabaey, et al.

Radiology reports convey detailed clinical observations and capture diagnostic reasoning that evolves over time. However, existing evaluation methods are limited to single-report settings and rely on coarse metrics that fail to capture fine-grained …
Published: Jan. 11, 2026. Version: 1.0.0
Database Credentialed Access

EchoGraph-annotated ECHO-NOTE2NUM examples

Chieh-Ju Chao, Mohammad Asadi

This repository releases the EchoGraph-annotated ECHO-NOTE2NUM dataset, containing 45,794 echocardiography reports with comprehensive entity and relation annotations. Each report from the ECHO-NOTE2NUM dataset has been automatically annotated using …
Published: Dec. 3, 2025. Version: 1.0.0
Database Contributor Review

ER-REASON: A Benchmark Dataset for LLM-Based Clinical Reasoning in the Emergency Room

Mel Molina, Nikita Mehandru, Niloufar Golchini, et al.

The ER-Reason dataset is a benchmark designed to evaluate LLM-based clinical reasoning and decision-making in the emergency room (ER), a high-stakes setting where clinicians make rapid, consequential decisions across diverse patient presentations an…
Published: Oct. 23, 2025. 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, et al.

Recent progress in Large Vision-Language Models (LVLMs) has enabled promising applications in medical tasks such as report generation and visual question answering. However, existing benchmarks focus mainly on the final diagnostic answer, offering l…
Published: Oct. 23, 2025. Version: 1.0.1
Database Credentialed Access

CXR-Align: A Benchmark for CXR-Report Alignment with Negations

Hanbin Ko

CXR-Align is a benchmark dataset designed to evaluate vision-language processing (VLP) models' ability to accurately interpret negations in chest X-ray (CXR) reports. Negations are prevalent in medical documentation and pose significant challenges f…
Published: Aug. 21, 2025. Version: 1.0.0
Database Credentialed Access

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

Amin Dada, Osman Alperen Koras, Marie Bauer, et al.

While increasing patients' access to medical documents improves medical care, this benefit is limited by varying health literacy levels and complex medical terminology. Large language models (LLMs) offer solutions by simplifying medical information.…
Published: May 5, 2025. Version: 1.0.0
Database Credentialed Access

A Temporal Dataset for Respiratory Support in Critically Ill Patients

Mira Moukheiber, Lama Moukheiber, Dana Moukheiber, et al.

We present a temporal benchmark dataset for clinical respiratory intervention tasks in intensive care unit (ICU) patients, derived from the MIMIC-IV v2.2 dataset. The data consists of 50,920 adult ICU patients and includes 90-day hourly ventilation …
Published: April 15, 2025. Version: 1.1.0
Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

Local annotation of medical data is both expensive and time-consuming due to the high cost of expert annotators, the precision required for accurate annotation, and the inherent challenges of medical diagnosis. To address these problems, we develop…
Published: Feb. 4, 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, et al.

The task of Difference Visual Question Answering involves answering questions about the difference between a pair of main and reference images. This process is consistent with the radiologist's diagnosis practice that compares the current image with…
Published: Feb. 3, 2025. Version: 1.0.1