Evidence map›Paper›PMID 41318466›Full record

ArticleBMC oral health2025

Development trend of Artificial Intelligence (AI) in dentistry: exploring FDA-cleared dental devices.

Nighat Naved, Samira Adnan, Fahad Umer

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nighat NavedAga Khan University Hospital, Karachi, Pakistan.ORCID 0000-0003-4994-5841
Samira AdnanCollege of Dentistry, King Faisal University, Al Ahsa , Kingdom of Saudi Arabia.ORCID 0000-0002-7866-4339
Fahad UmerAga Khan University Hospital, Karachi, Pakistan. fahad.umer@aku.edu.ORCID 0000-0003-3817-5941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionArtificial 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. MATERIALS AND

methodsA 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.

resultsFifty-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).

conclusionMost 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.

Indexed as

Artificial IntelligenceDentistryDevice ApprovalHumansMachine LearningUnited StatesUnited States Food and Drug Administration510(k) databaseArtificial intelligenceDentistryFDA cleared devicesMachine learningRegulatory approval

Identifiers

PMID41318466
PMCPMC12772014

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.