Development trend of Artificial Intelligence (AI) in dentistry: exploring FDA-cleared dental devices.
Authors
Affiliations (3)
Affiliations (3)
- Aga Khan University Hospital, Karachi, Pakistan.
- College of Dentistry, King Faisal University, Al Ahsa , Kingdom of Saudi Arabia.
- Aga Khan University Hospital, Karachi, Pakistan. [email protected].
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) are increasingly being incorporated into dentistry to enhance diagnostics, treatment planning, and clinical outcomes. However, their translation into routine practice is contingent upon regulatory approval to ensure safety and effectiveness. In the United States, the Food and Drug Administration (FDA) typically evaluates moderate-risk AI/ML-based dental devices under the 510(k) Premarket Notification pathway. Understanding the approval trends and characteristics of these devices is crucial for assessing the clinical integration of AI in dentistry. A manual search of the FDA's 510(k) Premarket Notification Database was conducted in December 2024 using the terms "AI/ML devices" and "dentistry." Devices were screened for relevance, and data were extracted regarding applicant name, device type, predicate device, year of approval, AI algorithm employed, clinical indication, country of origin, and status of real-world deployment. Fifty-two AI/ML dental devices were identified. The year 2022 saw the highest number of approvals (n = 8, 15.38%). Nearly half (n = 25, 48%) of the devices were indicated for oral radiology, followed by applications in implantology and regenerative procedures (n = 18, 32%). Overjet, Inc. received four approvals for diagnostic tools targeting caries, calculus, and charting. Ewoosoft Co., Ltd. accounted for six approvals, primarily versions of its Ez3D-i imaging platform. Most devices originated from the United States (n = 24, 46.15%), followed by South Korea (n = 5, 9.61%) and Canada (n = 3, 5.76%). Notably, 60% of devices did not disclose the type of AI/ML algorithm used (n = 31), and 50% lacked public documentation on clinical deployment (n = 26). Most FDA-cleared AI/ML dental devices in the 510(k) database are imaging-based diagnostics; greater transparency, real-world validation, and attention to equity are needed for safe adoption.