Resources

32 results for "deep learning"

Database Credentialed Access

MIMIC-IV-ECHO-Ext-LVVOLUMES-A4C-ROI: Annotated Subset of Apical Four-Chamber Echocardiography for PoCUS-Style LV Volume and Function Analysis

Kamlin Ekambaram, Anurag Arnab, Philip Herbst, et al.

MIMIC-IV-ECHO-Ext-LVVOLUMES-A4C-ROIis a curated, credentialed subset of MIMIC-IV-ECHO v0.1 focusing on apical four-chamber (A4C) echocardiographic views with accompanying left-ventricular volumetric labels. The release includes 1,064 de-identified A…
Published: Feb. 26, 2026. Version: 1.0.0
Challenge Credentialed Access

CXR-LT: Multi-Label Long-Tailed Classification on Chest X-Rays

Gregory Holste, Mingquan Lin, Song Wang, et al.

Chest radiography presents a "long-tailed" distribution of findings, where a few diseases are common, but most are rare. Diagnosis is further complicated by its multi-label nature, as patients often exhibit multiple co-occurring findings. While rece…
Published: March 19, 2025. Version: 2.0.0
Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

Electronic Health Records (EHRs), which contain patients' medical histories in various multi-modal formats, often overlook the potential for joint reasoning across imaging and table modalities underexplored in current EHR Question Answering (QA) sys…
Published: July 23, 2024. Version: 1.0.0
Database Credentialed Access

MIMIC-Ext-MIMIC-CXR-VQA: A Complex, Diverse, And Large-Scale Visual Question Answering Dataset for Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, et al.

We introduce MIMIC-Ext-MIMIC-CXR-VQA (i.e., Extended from MIMIC database), a complex, diverse, and large-scale dataset designed for Visual Question Answering (VQA) tasks within the medical domain, focusing primarily on chest radiographs. This datase…
Published: July 19, 2024. Version: 1.0.0
Database Restricted Access

CheXchoNet: A Chest Radiograph Dataset with Gold Standard Echocardiography Labels

Pierre Elias, Shreyas Bhave

Existing chest radiograph datasets, such as CheXpert and ChestX-ray14, have driven the development of new machine learning approaches to achieve expert or near-expert level performance on a variety of tasks. The primary focus of models developed usi…
Published: March 20, 2024. Version: 1.0.0
Database Credentialed Access

MIMIC-CXR-JPG - chest radiographs with structured labels

Alistair Johnson, Matthew Lungren, Yifan Peng, et al.

The MIMIC Chest X-ray JPG (MIMIC-CXR-JPG) Database v2.0.0 is a large publicly available dataset of chest radiographs in JPG format with structured labels derived from free-text radiology reports. The MIMIC-CXR-JPG dataset is wholly derived from MIMI…
Published: March 12, 2024. Version: 2.1.0
Database Credentialed Access

Nosocomial Risk Datasets from MIMIC-III

Travis Goodwin

Reliable longitudinal risk prediction for hospitalized patients is needed to provide quality care. Our goal is to foster the development of generalizable models capable of leveraging clinical notes to predict healthcare-associated diseases 24–96 hou…
Published: Sept. 15, 2022. Version: 1.0
Database Open Access

Haaglanden Medisch Centrum sleep staging database

Diego Alvarez-Estevez, Roselyne Rijsman

A collection of 151 whole-night polysomnographic (PSG) sleep recordings (85 Male, 66 Female, mean Age of 53.9 ± 15.4) collected during 2018 at the Haaglanden Medisch Centrum (HMC, The Netherlands) sleep center. Patient recordings were randomly selec…
Published: March 18, 2022. Version: 1.1 | Visualize waveforms
Database Open Access

A multi-camera and multimodal dataset for posture and gait analysis

Manuel Palermo, João Mendes Lopes, João André, et al.

Gait and posture analysis while using assisting robotic devices is of utmost importance to attain effective assistance. This work provides a multi-camera, multimodal, and detailed dataset for vision-based applications using a wheeled robotic walker …
Published: Nov. 1, 2021. 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, et al.

Labels localizing anomalies are rare in current chest x-rays datasets. We collected a dataset, using a method that can potentially be scaled up, to be a proof-of-concept for collecting implicit localization data through an eye-tracker. This dataset,…
Published: Sept. 27, 2021. Version: 1.0.0