Resources


Database Restricted Access

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

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection localization image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models

Published: Feb. 4, 2025. Version: 1.0.0

Database Contributor Review

COVID Data for Shared Learning (CDSL): A comprehensive, multimodal COVID-19 dataset from HM Hospitales

Álvaro Ritoré, Andreea M Oprescu, Alberto Estirado Bronchalo, Miguel Ángel Armengol de la Hoz

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified structured health data and radiological images from 4,479 patients with COVID-19, as a comprehensive toolkit for developing predictive models.

covid-19 multimodal database radiological images open data healthcare data machine learning and ai

Published: Oct. 25, 2024. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, Seth Berkowitz, Steven Horng

Chest radiographs in DICOM format with associated free-text reports.

computer vision chest x-rays natural language processing mimic machine learning radiology

Published: July 23, 2024. Version: 2.1.0

Database Credentialed Access

MS-CXR-T: Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Pérez-García, Max Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anton Schwaighofer, Maria Teodora Wetscherek, Hannah Richardson, Tristan Naumann, Javier Alvarez Valle, Ozan Oktay

The MS-CXR-T is a multimodal benchmark that enhances the MIMIC-CXR v2 dataset by including expert-verified annotations. Its goal is to evaluate biomedical visual-language processing models in terms of temporal semantics extracted from image and text.

disease progression cxr vision-language processing chest x-ray radiology multimodal

Published: March 17, 2023. Version: 1.0.0

Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Matthew Tong, Arjun Sharma, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth Krupinski, Mehdi Moradi

This dataset was a collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data.

convolutional network heatmap eye tracking explainability audio chest cxr chest x-ray machine learning radiology deep learning multimodal

Published: Sept. 12, 2020. Version: 1.0.0

Database Open Access

ReXErr-v1: Clinically Meaningful Chest X-Ray Report Errors Derived from MIMIC-CXR

Vishwanatha Rao, Serena Zhang, Julian Acosta, Subathra Adithan, Pranav Rajpurkar

Chest X-Ray reports containing synthetic errors based upon the MIMIC-CXR database. Errors were injected using LLMs and sampled across common human and AI model errors.

Published: March 19, 2025. Version: 1.0.0

Database Restricted Access

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

Elham Ghelichkhan, Tolga Tasdizen

This dataset includes bounding box-statement pairs for chest X-ray images, derived from radiologists’ eye-tracking data (for explainability) and annotations, for local visual-language models.

eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection localization image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models

Published: Feb. 4, 2025. Version: 1.0.0

Database Contributor Review

COVID Data for Shared Learning (CDSL): A comprehensive, multimodal COVID-19 dataset from HM Hospitales

Álvaro Ritoré, Andreea M Oprescu, Alberto Estirado Bronchalo, Miguel Ángel Armengol de la Hoz

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified structured health data and radiological images from 4,479 patients with COVID-19, as a comprehensive toolkit for developing predictive models.

covid-19 multimodal database radiological images open data healthcare data machine learning and ai

Published: Oct. 25, 2024. Version: 1.0.0

Database Credentialed Access

MIMIC-CXR Database

Alistair Johnson, Tom Pollard, Roger Mark, Seth Berkowitz, Steven Horng

Chest radiographs in DICOM format with associated free-text reports.

computer vision chest x-rays natural language processing mimic machine learning radiology

Published: July 23, 2024. Version: 2.1.0

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, Artur Conesa, Elisa Asensio, Antonio Lopez-Rueda, Helena Arino, Elena Calvo, Maria Jesús Bertran, Maria Angeles Marcos, Montserrat Nofre Maiz, Laura Tañá Velasco, Antonia Marti, Ricardo Farreres, Xavier Pastor, Xavier Borrat Frigola, Martin Krallinger

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