Resources


Database Credentialed Access

PIFIR: PET-CT Invasive Fungal Infection Reports

Vlada Rozova, Anna Khanina, Jeremy Ong, et al.

A corpus of PET-CT 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: Feb. 27, 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 image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization

Published: Feb. 4, 2025. Version: 1.0.0

Database Restricted Access

Application of Med-PaLM 2 in the refinement of MIMIC-CXR labels

Kendall Park, Rory Sayres, Andrew Sellergren, et al.

This work further refines the labels associated with CheXpert in MIMIC-CXR-JPG 2.0.0 by filtering with Med-PaLM 2 followed by verification by manual review by three US board-certified radiologists.

mimic-cxr labels

Published: Feb. 4, 2025. Version: 1.0.0

Database Restricted Access

TAME Pain: Trustworthy AssessMEnt of Pain from Speech and Audio for the Empowerment of Patients

Tu-Quyen Dao, Eike Schneiders, Jennifer Williams, et al.

TAME Pain is a dataset that captures acoustic signals of pain and is augmented by annotating every sentence the participant speaks with details such as background and foreground noise, speech errors, and non-speech vocal features.

audio speech pain cold pressor task

Published: Jan. 21, 2025. Version: 1.0.0

Database Restricted Access

MIMIC-IV-Ext-DiReCT

Bowen Wang, Jiuyang Chang, Yiming Qian

A diagnostic reasoning dataset designed to evaluate the performance of large language models in aligning with human doctors when making diagnoses from clinical notes.

Published: Jan. 21, 2025. Version: 1.0.0

Database Credentialed Access

Northwestern ICU (NWICU) database

Dana Moukheiber, William Temps, Bhadrappa Molgi, et al.

A freely available COVID-rich ICU database comprising de-identified health-related data from Northwestern Memorial Health Center (NHMC).

Published: Nov. 19, 2024. Version: 0.1.0

Model Credentialed Access

Shareable Artificial Intelligence to Extract Cancer Outcomes from Electronic Health Records for Precision Oncology Research

Kenneth Kehl, Pavel Trukhanov, Christopher Fong, et al.

The DFCI-imaging-student and DFCI-medonc-student AI models for extracting cancer outcomes from imaging reports and medical oncologist notes from electronic health records.

Published: Oct. 24, 2024. Version: 1.0.0

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, et al.

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

Database Open Access

MIMIC-IV Clinical Database Demo

Alistair Johnson, Lucas Bulgarelli, Tom Pollard, et al.

An openly available subset of patients in the MIMIC-IV database.

critical care electronic health record mimic

Published: Jan. 31, 2023. Version: 2.2

Database Credentialed Access

Learning to Ask Like a Physician: a Discharge Summary Clinical Questions (DiSCQ) Dataset

Eric Lehman

Dataset of questions asked by medical experts about patients. Medical experts will read a discharge summary line-by-line and (1) ask any question that they may have and (2) record what in the text "triggered" them to ask their question.

question generation question answering machine learning

Published: July 28, 2022. Version: 1.0