2330718
Cooperative Agreement
Overview
Grant Description
SBIR Phase II: Geometric Unified Learning - DIMSUM for Healthcare: Trust, Patient Focus, Collaboration, Privacy, and Cost-Efficiency
The broader impact of this Small Business Innovation Research (SBIR) Phase II project encompasses both societal and commercial sectors.
This project, centered around advancing healthcare technology, aims to significantly revolutionize the way healthcare providers approach diagnosing, monitoring, screening, and updating medical treatments.
The core innovation of this project lies in its ability to facilitate early and precise disease detection, thereby potentially reducing healthcare costs and markedly improving patient outcomes, especially in managing chronic and age-related health conditions.
In the commercial realm, this technology is set to make a substantial impact within the rapidly expanding healthcare AI market.
Its unique approach to processing and interpreting complex health data positions it as a groundbreaking advancement in healthcare AI.
Furthermore, this project can lead to enhanced scientific understanding and technological capabilities in the healthcare sector.
The project's success can result in efficient, accessible, and enhanced patient-centric healthcare delivery.
This is crucially needed in a world where healthcare systems are increasingly strained and the need for innovative solutions is ever-growing.
This Small Business Innovation Research (SBIR) Phase II project is focused on the development and refinement of a healthcare technology platform that utilizes Geometric Unified Learning.
This innovative approach is geared towards enhancing the efficiency and accuracy of healthcare diagnostics and monitoring.
The project aims to address the significant challenge of processing and interpreting complex health care data, particularly focusing on diseases that can be diagnosed and monitored using minimal yet crucial data sources such as voice and EEG.
The research objectives include refining the platform to handle real-world patient data effectively and expanding its capabilities to diagnose and monitor a broader range of diseases.
The development of a versatile, user-friendly, and effective diagnostic tool is expected to set new benchmarks in the field of healthcare AI.
Such a tool would not only provide significant advancements in medical diagnostics and patient care but would also contribute to the overall understanding of disease patterns and healthcare needs.
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.
Subawards are not planned for this award.
The broader impact of this Small Business Innovation Research (SBIR) Phase II project encompasses both societal and commercial sectors.
This project, centered around advancing healthcare technology, aims to significantly revolutionize the way healthcare providers approach diagnosing, monitoring, screening, and updating medical treatments.
The core innovation of this project lies in its ability to facilitate early and precise disease detection, thereby potentially reducing healthcare costs and markedly improving patient outcomes, especially in managing chronic and age-related health conditions.
In the commercial realm, this technology is set to make a substantial impact within the rapidly expanding healthcare AI market.
Its unique approach to processing and interpreting complex health data positions it as a groundbreaking advancement in healthcare AI.
Furthermore, this project can lead to enhanced scientific understanding and technological capabilities in the healthcare sector.
The project's success can result in efficient, accessible, and enhanced patient-centric healthcare delivery.
This is crucially needed in a world where healthcare systems are increasingly strained and the need for innovative solutions is ever-growing.
This Small Business Innovation Research (SBIR) Phase II project is focused on the development and refinement of a healthcare technology platform that utilizes Geometric Unified Learning.
This innovative approach is geared towards enhancing the efficiency and accuracy of healthcare diagnostics and monitoring.
The project aims to address the significant challenge of processing and interpreting complex health care data, particularly focusing on diseases that can be diagnosed and monitored using minimal yet crucial data sources such as voice and EEG.
The research objectives include refining the platform to handle real-world patient data effectively and expanding its capabilities to diagnose and monitor a broader range of diseases.
The development of a versatile, user-friendly, and effective diagnostic tool is expected to set new benchmarks in the field of healthcare AI.
Such a tool would not only provide significant advancements in medical diagnostics and patient care but would also contribute to the overall understanding of disease patterns and healthcare needs.
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.
Subawards are not planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH PHASE II (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23516
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Clifton,
Virginia
20124-1317
United States
Geographic Scope
Single Zip Code
Dasion Corporation was awarded
Cooperative Agreement 2330718
worth $999,988
from National Science Foundation in August 2024 with work to be completed primarily in Clifton Virginia United States.
The grant
has a duration of 2 years and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Cooperative Agreement was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase II Programs (SBIR/STTR Phase II).
SBIR Details
Research Type
SBIR Phase II
Title
SBIR Phase II: Geometric Unified Learning - DiMSuM for HealthCare: Trust, Patient Focus, Collaboration, Privacy, and Cost-Efficiency
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project encompasses both societal and commercial sectors. This project, centered around advancing healthcare technology, aims to significantly revolutionize the way healthcare providers approach diagnosing, monitoring, screening, and updating medical treatments. The core innovation of this project lies in its ability to facilitate early and precise disease detection, thereby potentially reducing healthcare costs and markedly improving patient outcomes, especially in managing chronic and age-related health conditions. In the commercial realm, this technology is set to make a substantial impact within the rapidly expanding healthcare AI market. Its unique approach to processing and interpreting complex health data positions it as a groundbreaking advancement in healthcare AI. Furthermore, this project can lead to enhanced scientific understanding and technological capabilities in the healthcare sector. The project’s success can result in efficient, accessible, and enhanced patient-centric healthcare delivery. This is crucially needed in a world where healthcare systems are increasingly strained and the need for innovative solutions is ever-growing.
This Small Business Innovation Research (SBIR) Phase II project is focused on the development and refinement of a healthcare technology platform that utilizes Geometric Unified Learning. This innovative approach is geared towards enhancing the efficiency and accuracy of healthcare diagnostics and monitoring. The project aims to address the significant challenge of processing and interpreting complex health care data, particularly focusing on diseases that can be diagnosed and monitored using minimal yet crucial data sources such as voice and EEG. The research objectives include refining the platform to handle real-world patient data effectively and expanding its capabilities to diagnose and monitor a broader range of diseases. The development of a versatile, user-friendly, and effective diagnostic tool is expected to set new benchmarks in the field of healthcare AI. Such a tool would not only provide significant advancements in medical diagnostics and patient care but would also contribute to the overall understanding of disease patterns and healthcare needs.
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.
Topic Code
AI
Solicitation Number
NSF 23-516
Status
(Ongoing)
Last Modified 8/27/24
Period of Performance
8/15/24
Start Date
7/31/26
End Date
Funding Split
$1000.0K
Federal Obligation
$0.0
Non-Federal Obligation
$1000.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2330718
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
HACYKENLMN35
Awardee CAGE
8JJL6
Performance District
VA-10
Senators
Mark Warner
Timothy Kaine
Timothy Kaine
Modified: 8/27/24