Assessing an AI-driven remote monitoring system for reliable clinical photo acquisition and patient usability
The study found that DM was user-friendly for all participants and that the photosets produced by the DM scans were substantially equivalent to the clinical live assessments conducted by dental experts. This suggests that DM is a highly reliable AIDRM tool, allowing healthcare professionals and patients to consistently produce high-quality image sets without requiring assistance or prior experience. This achievement opens the door to a new paradigm in orthodontic patient follow-up and may bring new dental prevention and treatment follow-up strategies.
Authors
- Mohammed H. Elnagar (ORCID: https://orcid.org/0000-0002-2332-9250)
- Michael Becher (ORCID: https://orcid.org/0000-0002-0072-1655)
- Rayan Skafi
- Hilary Nieberg-Baskin
- Zachary Joseph Mellion
- Blake R Borello
- Brian Wilk
Institutions
- Tanta University (EG)
- American Association of Orthodontists (US)
- University of Illinois Chicago (US)
- Rocky Mountain Orthodontics (United States) (US)
Publication Details
- Journal
- Journal of the World Federation of Orthodontists
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1016/j.ejwf.2025.08.002
- Citations
- 2
- Primary Topic
- Digital Imaging in Medicine
- Type
- article
- Field-Weighted Citation Impact
- 3.76