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Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/91239, first published .
Mobile Imaging–Based Machine Learning for Dental Caries, Sealants, and Fluorosis: Protocol for a Cross-Sectional Model Development and Validation Study

Mobile Imaging–Based Machine Learning for Dental Caries, Sealants, and Fluorosis: Protocol for a Cross-Sectional Model Development and Validation Study

Mobile Imaging–Based Machine Learning for Dental Caries, Sealants, and Fluorosis: Protocol for a Cross-Sectional Model Development and Validation Study

Sang Mok Park   1 * , PhD ;   Semin Kwon   1 * , PhD ;   Shaun G Hong   1 * , MS ;   Yuhyun Ji   1 , PhD ;   Sreeram P Nagappa   1 , MS ;   Jung Woo Leem   1 , PhD ;   Mei Lin   2 , MPH, MD ;   Eugenio D Beltrán-Aguilar   3, 4 , DMD, MPH, DrPH, DABDPH ;   Susan O Griffin   5 , PhD ;   Young L Kim   1, 6, 7 , PhD

1 Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States

2 Dental Public Health Consultant, Atlanta, GA, United States

3 Department of Epidemiology and Health Promotion, New York University, New York, NY, United States

4 Department of Oral Health Sciences, Kornberg School of Dentistry, Temple University, Philadelphia, PA, United States

5 TIS Consulting Group, State College, PA, United States

6 Purdue Institute for Cancer Research, Purdue University, West Lafayette, IN, United States

7 Regenstrief Center for Healthcare Engineering, Purdue University, West Lafayette, IN, United States

*these authors contributed equally

Corresponding Author:

  • Young L Kim, PhD
  • Weldon School of Biomedical Engineering
  • Purdue University
  • 206 S. Martin Jischke Drive
  • West Lafayette, IN 47907
  • United States
  • Phone: 1 765 496 2445
  • Email: youngkim@purdue.edu