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Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information

Yael Bensoussan, Alexandros Sigaras, Anais Rameau, Olivier Elemento, Maria Powell, David Dorr, Philip Payne, Vardit Ravitsky, Jean-Christophe Bélisle-Pipon, Alistair Johnson, Ruth Bahr, Stephanie Watts, Donald Bolser, Jennifer Siu, Jordan Lerner-Ellis, Frank Rudzicz, Micah Boyer, Samantha Salvi Cruz, Yassmeen Abdel-Aty, Toufeeq Ahmed Syed, James Anibal, Stephen Aradi, Ana Sophia Martinez, Shaheen Awan, Steven Bedrick, Isaac Bevers, Rahul Brito, Selina Casalino, John Costello, Iris De Santiago, Enrique Diaz-Ocampo, Mohamed Ebraheem, Ellie Eiseman, Mahmoud Elmahdy, Emily Evangelista, Kenneth Fletcher, Alexander Gelbard, Anna Goldenberg, Karim Hanna, William Hersh, Lochana Jayachandran, Kaley Jenney, Kathy Jenkins, Stacy Jo, Ayush Kalia, Andrea Krussel, Elisa Lapadula, Chloe Loewith, Radhika Mahajan, Vrishni Maharaj, Siyu Miao, Matthew Mifsud, Marian Mikhael, Elijah Moothedan, Yosef Nafii, Tempestt Neal, Karlee Newberry, Evan Ng, Christopher Nickel, Trevor Pharr, Claire Premi-Bortolotto, JM Rahman, Sarah Rohde, Laurie Russell, Suketu Shah, Ahmed Shawkat, Elizabeth Silberholz, Duncan Sutherland, Venkata Swarna Mukhi, Jeffrey Tang, Jamie Toghranegar, Kimberly Vinson, Claire Wilson, Madeleine Zanin, Xijie Zeng, Theresa Zesiewicz, Robin Zhao, Pantelis Zisimopoulos, Satrajit Ghosh

A dataset of features from voice recordings and metadata to enable the development, benchmarking, and validation of clinically applicable machine-learning models for diagnosing a wide range of health conditions.

voice bridge2ai

Published: April 16, 2025. Version: 2.0.0

Database Open Access

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

Hyung-Chul Lee, Chul-Woo Jung

VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

waveform anesthesia vitaldb intraoperative biosignal ecg

Published: Sept. 21, 2022. Version: 1.0.0

Database Credentialed Access

Northwestern ICU (NWICU) database

Dana Moukheiber, William Temps, Bhadrappa Molgi, Yikuan Li, Alice Lu, Prasanth Nannapaneni, Abdulrahman Chahin, Sicheng Hao, Felipe Torres Fabregas, Leo Anthony Celi, Adrian Wong, Maxwell Lloyd, Xavier Borrat Frigola, Hyung-Chul Lee, Daniel Schneider, Tom Pollard, Yuan Luo, Abel Kho, Roger Mark

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

Database Credentialed Access

MIMIC-IV

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

Large database of de-identified health information from patients admitted to Beth Israel Deaconess Medical Center

critical care intensive care unit mimic machine learning

Published: Jan. 6, 2023. Version: 2.2

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: Sept. 19, 2019. Version: 2.0.0

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 dataset artificial intelligence

Published: June 17, 2022. Version: 1.1.0

Latest Resources

Database Restricted Access

Community-Acquired Pneumonia, Endotypes and Phenotypes (NACef): Prospective, observational cohort study of Translational Medicine

Luis Felipe Reyes, Natalia Sanabria-Herrera, Esteban Garcia Gallo

Community-Acquired Pneumonia (CAP) poses a significant health risk, linked to high in-hospital morbidity and mortality rates. The dataset includes clinical details of 768 CAP patients at Clinica Universidad de La Sabana, Colombia.

Published: June 9, 2025. Version: 2.0.0

Database Open Access

Hillel Yaffe Glaucoma Dataset (HYGD): A Gold-Standard Annotated Fundus Dataset for Glaucoma Detection

Or Abramovich, Hadas Pizem, Jonathan Fhima, Eran Berkowitz, Ben Gofrit, Jan Van Eijgen, Eytan Blumenthal, Joachim Behar

HYGD is a rigorously annotated fundus image dataset with gold-standard clinical labels designed to improve and benchmark deep learning models for accurate glaucoma detection.

ophthalmology retina dfi gold-standard gon fundus glaucoma

Published: June 3, 2025. Version: 1.0.0

Database Open Access

bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset

Boyla Mainsah, Chance Fleeting, Thomas Balmat, Eric Sellers, Leslie Collins

A collection of data from P300-based brain-computer interface studies.

brain-computer interface electroencephalography ieee p2731 working group standard amyotrophic lateral sclerosis p300 speller p300 event related potential oddball paradigm error-related potential

Published: May 19, 2025. Version: 1.0.0

Database Credentialed Access

MIMIC-IV-Ext Cardiac Disease

Jiawei Cao, Sendong Zhao

The subset of the MIMIC-IV dataset includes the examination results and diagnostic information of 4,761 cardiac disease patients. The examination results for each patient are listed separately as evidence for the final diagnosis.

Published: May 6, 2025. Version: 1.0.0

Database Credentialed Access

FDTooth: Intraoral Photographs and Cone-Beam Computed Tomography Images for Fenestration and Dehiscence Detection

Yanqi Yang, Xiaomeng LI, Keyuan Liu, Marawan Elbatel

FDTooth is a dataset containing intraoral photographs and cone-beam computed tomography (CBCT) images with annotations for automated detection of fenestration and dehiscence in anterior teeth.

Published: May 5, 2025. Version: 1.0.0

Database Credentialed Access

MeDiSumQA: Patient-Oriented Question-Answer Generation from Discharge Letters

Amin Dada, Osman Alperen Koras, Marie Bauer, Amanda Butler, Kaleb Smith, Jens Kleesiek, Julian Friedrich

MeDiSumQA is a dataset of patient-oriented QA pairs from MIMIC-IV discharge summaries, designed to evaluate LLMs in generating safe, patient-friendly medical responses for clinical QA and healthcare communication.

Published: May 5, 2025. Version: 1.0.0

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News

This repository is under review by NIH for potential modification in compliance with U.S. federal Administration directives.

March 27, 2025

This repository is under review by NIH for potential modification in compliance with U.S. federal Administration directives.

BioNLP @ACL 2025 Shared Task on Grounded Electronic Health Record Question Answering (ArchEHR-QA)

Feb. 26, 2025

The overarching goal of the ArchEHR-QA 2025 (pronounced "Archer") shared task is to develop automated responses to patients' questions by generating answers that are grounded in key clinical evidence from their electronic health records (EHRs). The proposed dataset, ArchEHR-QA, comprises hand-curated, realistic patient questions (reflective of patient portal messages), relevant focus areas identified within these questions (as determined by a clinician), corresponding clinician-rewritten versions (crafted to aid in formulating responses), and note excerpts providing essential clinical context.

New Dataset: Bridge2AI-Voice v1.0 Now Available on PhysioNet

Feb. 4, 2025

We are pleased to announce the release of Bridge2AI-Voice v1.0, a dataset designed to advance research into the use of voice as a biomarker of health. This dataset, developed as part of the NIH Bridge2AI initiative, aims to support artificial intelligence research by providing ethically sourced, high-quality voice-derived data linked to clinical information.

Bridge2AI-Voice v1.0 includes 12,523 voice-derived recordings from 306 participants across five North American sites. Participants were selected based on conditions known to affect vocal characteristics, including:

Voice disorders (e.g., laryngeal conditions affecting phonation)
Neurological and neurodegenerative disorders (e.g., Parkinson’s, ALS, stroke)
Mood and psychiatric disorders (e.g., depression, anxiety)
Respiratory disorders (e.g., asthma, chronic cough)
Pediatric voice and speech disorders

The initial release does not include raw voice recordings. Instead, it provides derived acoustic features, such as spectrograms, along with detailed demographic, clinical, and validated questionnaire data.

The George B. Moody PhysioNet Challenge 2025 has begun

Jan. 21, 2025

This year's Challenge focuses on detecting Chagas disease from ECGs. Chagas disease is a parasitic disease in Central and South America that affects an estimated 6.5 million people and causes nearly 10,000 deaths annually. Timely treatment may prevent or slow damage to the cardiovascular system, but serological testing capacity is limited, so detection through ECGs can help to identify potential Chagas patients for testing and treatment.

MIMIC-IV v3.1 is now available on BigQuery

News from: MIMIC-IV v3.1.

Nov. 12, 2024

MIMIC-IV v3.1 is now available on BigQuery. Users may request access via PhysioNet. Currently, MIMIC-IV v3.1 is available on the mimiciv_v3_1_hosp and mimiciv_v3_1_icu schemas. MIMIC-IV v2.2 is available on the mimiciv_v2_2_hosp and mimiciv_v2_2_icu datasets as well as the mimiciv_hosp and mimiciv_icu datasets. On November 25th 2024, we will replace the data on mimiciv_hosp and mimiciv_icu with MIMIC-IV v3.1.

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