12/5/25, 9:08 PM

RePORT ⟩ RePORTER

NIH RePORTER Announcement:

A "No Cost Extension" indicator is now available on RePORTER! The indicator appears in the "Other Information"

section on the "Project Details" page.



RePORT

RePORTER

Project Details

 Share

 Description

 Details

 Sub-Projects

 Publications

 Patents

 Outcomes

 Clinical Studies

 News and More

 History

 Similar Projects



Bridge2AI: Patient-Focused Collaborative

Hospital Repository Uniting Standards

(CHoRUS) for Equitable AI

Project
Number

Contact
PI/Project

Awardee
Organization

1OT2OD032701-
01

Leader
ROSENTHAL,

ERIC S.
Other PIs

 Description

Abstract Text

Abstract Text There is an urgent need for infrastructure to
support artificial intelligence and machine learning

(AI/ML) in critical care. Developing high-resolution multi-
center data sets is a critical first step towards actionable
and trustworthy AI. As part of the NIH Common Fund’s
Bridge2AI program, the CPatient-Focused Collaborative

Hospital Repository Uniting Standards (CHoRUS) for
Clinical Care AI data generation project will meet the need
of generating data for ML/AI applications aimed at
characterizing acute and critical care illness, predicting
complications, and measuring treatment response among

https://reporter.nih.gov/project-details/10472824

Privacy  -  Terms

1/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

patients with acute or critical illness. Through 3 pillars, the

CHoRUS data generation project will addresses multiple

challenges relevant for acquiring an AI-ready data set

from more than 100,000 critically ill patients: 1) Data

(Standards, Tool Development and Optimization, and Data

Acquistion) 2) Ethics (Ethical and Trustworthy AI) and 3)

People (Team Science and Skill and Workforce

Development). The project’s overarching goal is to

develop a publicly available, AI-ready critical care dataset,

while ensuring the methods promote privacy,

accountability, and clinical benefit, while promoting a new

generation of AI clinicians and scientists. The dataset will

also provision a holdout test set, accessible for model

external validation to aid marketplace adoption of AI-

developed models for implementation in acute and
critical care. Drawing expertise from a comprehensive set
of disciplines such as team science, law, ethics, health
services, biomedical science, engineering, and scientific
journal publications, this project will A) establish a legal
framework for collecting data at scale, sampling to ensure

comprehensive sets of patient conditions and clinical
treatment strategies; B) perform community-facing ethics
focus groups to determine what data is appropriate for
public sharing; C) ensure that data elements feature
appropriate contextual factors such as geographic
distance to the nearest hospital; D) develop capabilities
across a multi-center network to acquire, standardize,
tokenize, store, visualize, and label data such as

structured electronic health record data, tokenized
unstructured electronic health record data, telemetry and
EEG waveforms, imaging, and social determinants of
health; E) acquire data, standardize data to the OMOP
Common Data Model, transform data using approaches
that limit re-identification, and label data for ; and F)
cultivate expertise in the lay and scientific community to
improve AI literacy nd utilization through multimodal
educational approaches. To accomplish this, the project

will involve extensive collaboration between centers as
well as through the NIH Bridge2AI program, the NIH

https://reporter.nih.gov/project-details/10472824

2/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

Bridge2AI Bridge Center, external biomedical and clinical

organizations, industry, and regulatory agencies.

Public Health Relevance Statement

The Patient-Focused Collaborative Hospital Repository

Uniting Standards (CHoRUS) for Equitable AI will develop

the necessary network, tools, standards, data, and

education to build machine-learning (ML) and artificial

intelligence (AI)-derived models to improve the care and

outcomes of patients requiring critical care. By

performing legal and ethical research, developing tools

for data storage, labeling and analysis, acquiring and

standardizing a dataset of unprecedented diversity and

high resolution, sequestering holdout datasets for
external validation, and enriching the community through
education, this data generation project will catalyze the
biomedical research and expertise necessary to promote
the patient-focused deployment of AI in acute and critical
care.

NIH Spending Category

Bioengineering

Clinical Research

Data Science

Machine Learning and Artificial Intelligence

Networking and Information Technology R&D
(NITRD)

Social Determinants of Health

Project Terms

Accountability

Acute

Address

Adoption

Artificial Intelligence

Biomedical Research

Bridge to Artificial Intelligence

Clinical

https://reporter.nih.gov/project-details/10472824

3/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

Collaborations

Communities

Critical Care

Critical Illness

Data

Data Element

Data Set

Data Storage and Retrieval

Deterioration

Diagnosis

Discipline

Education
Read More

Electroencephalography

 Details

Contact PI/
Project
Leader

Name
ROSENTHAL,
ERIC S. 



Title
DIRECTOR,
MGH
NEUROSCIENCES
ICU

Contact

View
Email

Program
Official

Name
KUXHAUS,
LAUREL
CATHERINE

Contact

View
Email

Other PIs

Name
BIHORAC,
AZRA 

CORDES,
ASHLEY 

CLERMONT,
GILLES 

CLIFFORD,
GARI DAVID
EVANS,

BARBARA J.
HU, XIAO


KAMALESWARAN,
RISHIKESAN
LEVITES

STREKALOVA,
YULIA A. 
RASHIDI,
PARISA 
RUDIN,
CYNTHIA 
WILLIAMS,
ISHAN
CANTY 

WILLIAMS,
ANDREW
EWING 








Organization

Name
MASSACHUSETTS GENERAL HOSPITAL

City

https://reporter.nih.gov/project-details/10472824

4/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

BOSTON

Country
UNITED STATES (US)

Department Type
Unavailable

Organization Type
Independent Hospitals

State Code
MA

Congressional District
08

Other Information

Opportunity Number
OTA-21-008

Study Section
Data Coordination, Mapping, and Modeling[DCMM]

Fiscal Year
2022

Award Notice Date
01-September-2022

Administering Institutes or Centers
NIH Office of the Director

Assistance Listing Number
93.310

DUNS Number
073130411
UEI
FLJ7DQKLL226

Project Start Date

01-September-2022

Project End Date

30-November-2026

Budget Start Date
01-September-2022

Budget End Date
30-November-2026

https://reporter.nih.gov/project-details/10472824

5/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

No Cost Extension
Y

Project Funding Information for 2022

Total Funding
$5,880,300

Direct Costs
$5,880,300

Indirect Costs

Year
Year

Funding IC

Funding IC

FY Total Cost by IC

2022 NIH Office of the Director

$5,880,300

NIH Categorical Spending
Click here for more information on NIH Categorical

Spending

Funding
IC

FY Total Cost by IC NIH Spending Category

RM

$5,880,300

101; 176; 4531; 4372; 329;
4793

 Sub Projects

No Sub Projects information available for
1OT2OD032701-01

 Publications

 Disclaimer

https://reporter.nih.gov/project-details/10472824

6/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

No Publications available for 1OT2OD032701-01

 Patents

No Patents information available for
1OT2OD032701-01

 Outcomes

The Project Outcomes shown here are displayed verbatim as submitted
by the Principal Investigator (PI) for this award. Any opinions, findings,
and conclusions or recommendations expressed are those of the PI
and do not necessarily reflect the views of the National Institutes of
Health. NIH has not endorsed the content below.

No Outcomes available for 1OT2OD032701-01

 Clinical Studies

No Clinical Studies information available for
1OT2OD032701-01

 News and More

Related News Releases

No news release information available for

https://reporter.nih.gov/project-details/10472824

7/8

12/5/25, 9:08 PM

RePORT ⟩ RePORTER

1OT2OD032701-01

 History

No Historical information available for
1OT2OD032701-01

 Similar Projects

No Similar Projects information available for
1OT2OD032701-01

https://reporter.nih.gov/project-details/10472824

8/8

