Ensuring integrity in dental education: Developing a novel <scp>AI</scp> model for consistent and traceable image analysis in preclinical endodontic procedures
The AI-driven Siamese neural network effectively detects radiographic inconsistencies in RCT preclinical procedures. Implementing this novel model will serve as an objective tool to uphold academic integrity in dental education, enhance the fairness and reliability of assessments, promote a culture of honesty amongst students, and reduce the administrative burden on educators.
Authors
- Arndt Guentsch (ORCID: https://orcid.org/0000-0001-8989-1441)
- Joseph W. Gaffney
- Mohamed Ibrahim (ORCID: https://orcid.org/0000-0001-6504-5945)
- Meisam Omidi (ORCID: https://orcid.org/0000-0001-7534-9459)
- Jennifer Talley (ORCID: https://orcid.org/0000-0002-9833-7642)
Institutions
- Marquette University (US)
- Delta Air Lines (United States) (US)
Publication Details
- Journal
- International Endodontic Journal
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1111/iej.14273
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96