Abstract & Details
Description
Award ID: 2409580
This I-Corps project develops a centralized data management platform for health services researchers and data-resource related decision-makers at academic organizations. The technology provides data management and analytics tools to researchers to expedite their work and allow more time to focus on networking, scientific discovery, and innovation. In addition, the technology provides advanced data cleansing and preprocessing, and may be used with data solutions for the emerging synthetic data industry and generative artificial intelligence (AI) technologies. The platform's streamlined processes are designed to generate evidence-based knowledge that may be leveraged by healthcare administrators, policymakers, and decision-makers to enhance healthcare services. In the future, the platform may not only serve as a research tool but also facilitate data-informed decision-making capabilities for users. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of software technology that addresses the challenges health services researchers face with data aggregation, cleansing, integration, and maintenance from public and private sources. The technology uses a centralized data warehouse, providing analysis-ready data sets and alleviating researchers from repetitive data tasks. In addition, it refines aspects of data management by improving data acquisition, extraction, preprocessing, and cleansing phases using a mix of traditional statistical tools and advanced artificial intelligence (AI) algorithms. As the platform integrates new data sources and methodologies, it's designed to expand, ensuring scalability. This approach may save researchers time and resources, enabling them to focus on the intellectual pursuits of their research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Ruth Shuman
This I-Corps project develops a centralized data management platform for health services researchers and data-resource related decision-makers at academic organizations. The technology provides data management and analytics tools to researchers to expedite their work and allow more time to focus on networking, scientific discovery, and innovation. In addition, the technology provides advanced data cleansing and preprocessing, and may be used with data solutions for the emerging synthetic data industry and generative artificial intelligence (AI) technologies. The platform's streamlined processes are designed to generate evidence-based knowledge that may be leveraged by healthcare administrators, policymakers, and decision-makers to enhance healthcare services. In the future, the platform may not only serve as a research tool but also facilitate data-informed decision-making capabilities for users. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of software technology that addresses the challenges health services researchers face with data aggregation, cleansing, integration, and maintenance from public and private sources. The technology uses a centralized data warehouse, providing analysis-ready data sets and alleviating researchers from repetitive data tasks. In addition, it refines aspects of data management by improving data acquisition, extraction, preprocessing, and cleansing phases using a mix of traditional statistical tools and advanced artificial intelligence (AI) algorithms. As the platform integrates new data sources and methodologies, it's designed to expand, ensuring scalability. This approach may save researchers time and resources, enabling them to focus on the intellectual pursuits of their research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Ruth Shuman
| Status | Closed |
|---|---|
| Effective start/end date | 03/01/24 → 08/31/26 |
Funding
- I-Corps Teams: $50,000.00
Active Fiscal Year
- FY2024
- FY2026
- FY2025
Start Fiscal Year
- FY2024
TIP Programs
- I-Corps Teams
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
- Data and Cybersecurity
- (confidence score: 100%)
Technology Foci
- Data Management / Databases
- (confidence score: 100%)
- Artificial Intelligence (excluding ML)
- (confidence score: 99%)
Congressional District at Award
- District n. 07 of Alabama
Current Congressional District
- District n. 07 of Alabama
United States
- Alabama
Core Based Statistical Area (CBSA)
- Birmingham, AL
County
- County: Jefferson, AL
EPSCoR Jurisdiction
- Yes
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine