Brain Data Science Platform

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Database Restricted Access

The Boston Childrens Hospital Sleep Corpus

Ayush Tripathi, Wolfgang Ganglberger, Haoqi Sun, Callison Alcott, Niels Turley, Rebecca Fitzgerald, Ayan Mitra, Samuel Waters, Arnav Gupta, Aditya Gupta, Manohar Ghanta, Valdery Moura Junior, Samaneh Nasiri, Bruce Nearing, Katie Stone, Emmanuel Mignot, Dennis Hwang, Matthew Reyna, Zuzana Koscova, Chad Robichaux, Zhiyong Zhang, Qiao Li, Gauri Ganjoo, Lynn Marie Trotti, Gari Clifford, Christine Tsien Silvers, Bharath Gunapati, Robert Thomas, M Brandon Westover, Kiran Maski, Umakanth Katwa

The Boston Children’s Hospital (BCH) Sleep Corpus comprises 15,695 fully annotated pediatric polysomnography (PSG) recordings collected between 2010 and 2024.

Published: Aug. 6, 2025. Version: 1.0.1

Database Restricted Access

Cerebrospinal Fluid Testing for Neuroinvasive West Nile Virus and Measures to Improve Guideline Adherence

Carson Quinn, Karan Singh, Erik Klontz, Isaac Solomon, Shibani Mukerji

De-identified, dataset of 1,304 adult encounters with CSF-fluid West Nile virus testing patterns at two Mass General Brigham hospitals (2016-2023). Includes demographics, immune status, CSF/serum labs, WNV PCR & IgM results, guideline-adherence flags

Published: July 31, 2025. Version: 1.0.0

Database Credentialed Access

Harvard-Emory ECG Database

Zuzana Koscova, Valdery Moura Junior, Matthew Reyna, Shenda Hong, Aditya Gupta, Manohar Ghanta, Reza Sameni, Aaron Aguirre, Qiao Li, Sahar Zafar, Gari Clifford, M Brandon Westover

The Harvard ECG database (HEEDB) is a large collection of 12-lead electrocardiography (ECG) recordings.

Published: July 28, 2025. Version: 4.0

Database Credentialed Access

Identification of patients with epilepsy using automated electronic health records phenotyping - Data and Code

Marta Fernandes, Sahar Zafar, M Brandon Westover

Code and data for identifying patients with epilepsy using automated electronic health records.

ehr epilepsy nlp

Published: June 5, 2025. Version: 1.0

Database Credentialed Access

Automated phenotyping of mild cognitive impairment and dementias using electronic health records - Data and Code

Ruoqi Wei, Robert Thomas, M Brandon Westover, Haoqi Sun

Data and Code to reproduce results in "Automated phenotyping of mild cognitive impairment and dementias using electronic health records"

ad mci nlp

Published: June 5, 2025. Version: 1.0

Database Restricted Access

NIDX: A Machine Learning Approach for Identifying People with Neuroinfectious Diseases in Electronic Health Records

Arjun Singh, Shadi Sartipi, Haoqi Sun, Niels Turley, Sahar Zafar, Sudeshna Das, Marta Fernandes, M Brandon Westover, Shibani Mukerji

A machine learning approach to accurately identify neuroinfectious diseases from clinical notes.

electronic health records ehr phenotyping natural language processing neuroinfectious diseases

Published: May 31, 2025. Version: 1.0

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News

BDSP Recognized as NIH-Approved Data Repository

Nov. 21, 2024

As of Nov 21, 2024, the National Institutes of Health (NIH) has officially recognized BDSP as an approved repository for researchers to meet NIH Data Management and Sharing (DMS) requirements. This designation enables NIH-funded researchers to utilize BDSP for depositing and sharing their research data in compliance with NIH data sharing policies. As a vetted repository on the NIH's list of domain-specific repositories, BDSP is commited to advancing open science and facilitating collaborative research in brain data science.

For more information about depositing data in BDSP, please contact our support team.

Learn how to interact with the project data --- click here

Oct. 16, 2023

Take a look at the Tutorial explaining how to interact and download with the data published together with BDSP Projects. You can find more details here.

New I-CARE train dataset released !

News from: I-CARE: International Cardiac Arrest REsearch consortium Electroencephalography Database v1.0.

Oct. 16, 2023

The International Cardiac Arrest REsearch consortium (I-CARE) Database includes baseline clinical information and continuous electroencephalography (EEG) recordings from 1,020 comatose patients with a diagnosis of cardiac arrest who were admitted to an intensive care unit from seven academic hospitals in the U.S. and Europe. Patients were monitored with 18 bipolar EEG channels over hours to days for the diagnosis of seizures and for neurological prognostication. Long-term neurological function was determined using the Cerebral Performance Category scale.

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