Award Abstract # 2238208
SCC-IRG Track 1: Smart Connected Oral Health Community: Using AI and Digital Technologies to Close the Gap in Oral Health Disparity

NSF Org: SES
Division of Social and Economic Sciences
Recipient: UNIVERSITY OF ROCHESTER
Initial Amendment Date: June 15, 2023
Latest Amendment Date: June 15, 2023
Award Number: 2238208
Award Instrument: Standard Grant
Program Manager: Sara Kiesler
skiesler@nsf.gov
 (703)292-8643
SES
 Division of Social and Economic Sciences
SBE
 Directorate for Social, Behavioral and Economic Sciences
Start Date: June 15, 2023
End Date: May 31, 2026 (Estimated)
Total Intended Award Amount: $1,500,000.00
Total Awarded Amount to Date: $1,500,000.00
Funds Obligated to Date: FY 2023 = $1,500,000.00
History of Investigator:
  • Jiebo Luo (Principal Investigator)
    jluo@cs.rochester.edu
  • Timothy Dye (Co-Principal Investigator)
  • Jin Xiao (Co-Principal Investigator)
  • Michael Mendoza (Co-Principal Investigator)
  • Kevin Fiscella (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Rochester
910 GENESEE ST
ROCHESTER
NY  US  14611-3847
(585)275-4031
Sponsor Congressional District: 25
Primary Place of Performance: University of Rochester
500 JOSEPH C WILSON BLVD
ROCHESTER
NY  US  14627-0001
Primary Place of Performance
Congressional District:
25
Unique Entity Identifier (UEI): F27KDXZMF9Y8
Parent UEI:
NSF Program(s): S&CC: Smart & Connected Commun
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 042Z
Program Element Code(s): 033Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070, 47.075

ABSTRACT

Tooth decay is a pandemic disease that affects 35% of the global population, or 2.4 billion people. Dental caries (tooth decay) particularly impacts children and adults living in poverty, who have poor access to dental care. Current biomedical approaches to controlling dental caries have had limited success. This project is creating a smart, connected oral health community with improved access to care and greater oral health equity. The investigators aim to develop and test a community-based infrastructure that combines use of artificial intelligence (AI) technology, facilitated by home use of smartphones, with community engagement through interactive oral health community centers, mobile vans, and community health workers. The project has the potential to reform the oral health care delivery system, empower communities with digital tools, and overcome barriers to oral health equity. Beginning with a focus on families with young children, the model could also be adopted by other underserved populations, such as the elderly and refugees, who face similar challenges in accessing oral health care.

The project team is refining the underlying technology with AI-powered oral disease screening and management with cloud surveillance, and data collection facilitated by a dentistry smartphone app for at-home self-monitoring. The team is also investigating the social dimensions of the problem. It is establishing oral health community centers supported by community health workers who apply established methods of human motivation to reach and empower families in the community, and to teach and motivate them to use the new AI apps. The team will be assessing community outcomes of the project, with a focus on the use of technology tools for caries detection and treatment prioritization, and community engagement with services in oral health community centers. Outcomes will be measured by the perceived competence of providers and patients, and the technology's acceptance, usability, and effectiveness.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Al_Jallad, N and Manning, S and Mao, X and Mehta, P and Wu, T and Cacciato, R and Luo, J and Li, Y and Xiao, J "Identifying Patterns in Dental Visit Attendance Among Pregnant Women: A Retrospective Cohort Study" AJPM focus , 2025 Citation Details
Zeng, Z and Ramesh, A and Ruan, J and Hao, P and Al_Jallad, N and Jang, H and Ly-Mapes, O and Fiscella, K and Xiao, J and Luo, J "Use of artificial intelligence to detect dental caries on intraoral photos" Quintessence international , 2025 Citation Details

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