Resources


Database Credentialed Access

MedNLI for Shared Task at ACL BioNLP 2019

Chaitanya Shivade

Data for the MedNLI Shared Task at the 2019 ACL BioNLP 2019 Workshop on Biomedical Language Processing

mimic natural language inference recognizing textual entailment

Published: Nov. 28, 2019. Version: 1.0.1

Model Credentialed Access

Clinical-T5: Large Language Models Built Using MIMIC Clinical Text

Eric Lehman, Alistair Johnson

We train a T5-Base and T5-Large from scratch on MIMIC-III and MIMIC-IV. Additionally, we further pretrain T5-Base and SciFive on notes from MIMIC. We release these model weights on PhysioNet.

Published: Jan. 25, 2023. Version: 1.0.0

Model Credentialed Access

EntityBERT: BERT-based Models Pretrained on MIMIC-III with or without Entity-centric Masking Strategy for the Clinical Domain

Chen Lin, Steven Bethard, Guergana Savova, Timothy Miller, Dmitriy Dligach

Pretraining of models with a broad representation of biomedical terminology (PubMedBERT) on MIMIC-III corpus along with or without a novel entity-centric masking strategy.

Published: March 17, 2022. Version: 1.0.1

Challenge Credentialed Access

Analysis of Clinical Text: Task 14 of SemEval 2015

Guergana Savova

This is the dataset for SemEval 2014 and 2015, Analysis of Clinical Text

semeval nlp

Published: Dec. 28, 2014. Version: 2.0

Database Credentialed Access

CXR-PRO: MIMIC-CXR with Prior References Omitted

Vignav Ramesh, Nathan Chi, Pranav Rajpurkar

CXR-PRO is an adaptation of the MIMIC-CXR dataset (consisting of chest radiographs and their associated free-text radiology reports) with references to non-existent priors removed.

generation free-text radiology reports references to priors retrieval large language models

Published: Nov. 23, 2022. Version: 1.0.0

Database Credentialed Access

Tasks 1 and 3 from Progress Note Understanding Suite of Tasks: SOAP Note Tagging and Problem List Summarization

Yanjun Gao, John Caskey, Timothy Miller, Brihat Sharma, Matthew Churpek, Dmitriy Dligach, Majid Afshar

We introduce a hierarchical annotation suite of tasks addressing clinical text understanding, reasoning and abstraction over evidence, and diagnosis summarization. One task is section tagging major section and the other task is diagnosis generation.

Published: Sept. 30, 2022. Version: 1.0.0

Database Credentialed Access

CXR-PRO: MIMIC-CXR with Prior References Omitted

Vignav Ramesh, Nathan Chi, Pranav Rajpurkar

CXR-PRO is an adaptation of the MIMIC-CXR dataset (consisting of chest radiographs and their associated free-text radiology reports) with references to non-existent priors removed.

generation free-text radiology reports references to priors retrieval large language models

Published: Nov. 23, 2022. Version: 1.0.0

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

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, Arjun Sharma, Joseph Paguio, Jasper Seth Yao, Edward Christopher Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, Leo Anthony Celi, Tanveer Syeda-Mahmood, Mehdi Moradi

The Chest ImaGenome dataset is a scene graph dataset with additional chronological comparison relations for chest X-rays. It is automatically derived from the MIMIC-CXR dataset. A manually annotated gold standard is also available for 500 patients.

multimodal chest x-ray radiology machine learning scene graph visual dialogue object detection semantic reasoning bounding box relation extraction knowledge graph explainability reasoning chest cxr visual question answering deep learning disease progression

Published: July 13, 2021. Version: 1.0.0

Database Credentialed Access

RadGraph: Extracting Clinical Entities and Relations from Radiology Reports

Saahil Jain, Ashwin Agrawal, Adriel Saporta, Steven QH Truong, Du Nguyen Duong, Tan Bui, Pierre Chambon, Matthew Lungren, Andrew Ng, Curtis Langlotz, Pranav Rajpurkar

RadGraph is a dataset of entities and relations in full-text chest X-ray radiology reports, which are obtained using a novel information extraction (IE) schema to capture clinically relevant information in a radiology report.

entity and relation extraction graph multi-modal radiology natural language processing

Published: June 3, 2021. Version: 1.0.0