Resources


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 anonymization clinical ner

Published: Nov. 2, 2023. Version: 1.0


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.

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

Published: Sept. 12, 2020. 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.

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

Published: Sept. 12, 2020. Version: 1.0.0


Database Credentialed Access

CHIFIR: Cytology and Histopathology Invasive Fungal Infection Reports

Vlada Rozova, Anna Khanina, Jasmine Teng, Joanne Teh, Leon Worth, Monica Slavin, karin thursky, Karin Verspoor

A corpus of cytology and histopathology reports annotated for terminology relevant to fungal infections. Ideal for validation of named entity recognition and relation extraction methods.

nlp clinical documentation information extraction invasive fungal infections

Published: Nov. 2, 2023. Version: 1.0.1


Database Credentialed Access

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

Alistair Johnson, Tom Pollard, Steven Horng, Leo Anthony Celi, Roger Mark

Deidentified free-text clinical notes for patients in the MIMIC-IV Clinical Database.

mimic deidentification critical care electronic health record clinical notes natural language processing

Published: Jan. 6, 2023. Version: 2.2


Database Credentialed Access

BRAX, a Brazilian labeled chest X-ray dataset

Eduardo Pontes Reis, Joselisa Paiva, Maria Carolina Bueno da Silva, Guilherme Alberto Sousa Ribeiro, Victor Fornasiero Paiva, Lucas Bulgarelli, Henrique Lee, Paulo Victor dos Santos, vanessa brito, Lucas Amaral, Gabriel Beraldo, Jorge Nebhan Haidar Filho, Gustavo Teles, Gilberto Szarf, Tom Pollard, Alistair Johnson, Leo Anthony Celi, Edson Amaro

BRAX contains 24,959 chest radiography exams and 40,967 images acquired in a large general Brazilian hospital. All images have been read by trained radiologists and 14 labels were derived from Brazilian Portuguese reports using NLP.

chest x-ray artificial intelligence dataset

Published: June 17, 2022. Version: 1.1.0


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.

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

Published: Sept. 19, 2019. Version: 2.0.0


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.

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

Published: March 17, 2023. Version: 1.0.0


Database Restricted Access

REFLACX: Reports and eye-tracking data for localization of abnormalities in chest x-rays

Ricardo Bigolin Lanfredi, Mingyuan Zhang, William Auffermann, Jessica Chan, Phuong-Anh Duong, Vivek Srikumar, Trafton Drew, Joyce Schroeder, Tolga Tasdizen

This dataset contains 3032 cases of eye-tracking data collected while five radiologists dictated reports for frontal chest x-rays, synchronized timestamped dictation transcription, and manual labels for validation of localization of abnormalities.

computer vision eye tracking radiology report chest x-rays radiology machine learning reflacx fixations gaze deep learning

Published: Sept. 27, 2021. Version: 1.0.0


Database Credentialed Access

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

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

MS-CXR is a new dataset containing 1162 Chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

chest x-ray vision-language processing

Published: May 16, 2022. Version: 0.1