Videa Dental AI

K251002

VideaHealth Inc. · cleared 2025-09-19 · product code MYN · Radiology

FDA 510(k) summary for Videa Dental AI (K251002)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
2
Cited predicates
1
Performance observations
8
Product code
MYN

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.7)
“Videa Dental AI (VDA) software is a cloud-based AI-powered medical device for the automatic detection of the features listed in the Indications For Use statement in dental radiographs.”
AlgorithmSupervised Deep Learning
source quote (p.12)
“Supervised Deep Learning”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedNo

Validation studies (2)

Bench

n=1,445 images · 35 site(s)

standards: ISO 14971:2019 Application of Risk Management to Medical Devices., AAMI CR34971:2022 Guidance on the Application of ISO 14971 to Artificial Intelligence and Machine Learning, IEC 62304 Edition 1.1 2015-06 Consolidated Version: Medical Device Software - Software Life Cycle Processes, Good Machine Learning Practice for Medical Device Development: Guiding Principles October 2021., FDA Content of Premarket Submissions for Device Software Functions (June 14, 2023)

Reader study (MRMC)

n=378 images · 25 site(s)

endpoints: determine whether the diagnostic accuracy of readers aided by VDA is superior to reader accuracy when unaided by VDA, as determined by the AFROC Figure of Merit (AFROC FOM).

Reported performance (8 observations)

specificity0.867
source quote (p.15)
“VDA caries had a standalone specificity of 0.867 for caries' and 0.989 for PRL' second operating points respectively.”
diceas written: “DICE (caries)”0.72
source quote (p.14)
“VDA caries had a DICE of 0.720 and calculus had a DICE of 0.716 respectively.”
diceas written: “DICE (calculus)”0.716
source quote (p.14)
“VDA caries had a DICE of 0.720 and calculus had a DICE of 0.716 respectively.”
diceas written: “DICE (Enamel)”0.907
source quote (p.14)
“Enamel is 0.907”
diceas written: “DICE (Pulp)”0.825
source quote (p.14)
“Pulp is 0.825”
diceas written: “DICE (Crown Dentin)”0.878
source quote (p.14)
“Crown Dentin is 0.878”
diceas written: “DICE (Root Dentin)”0.874
source quote (p.14)
“Root Dentin is 0.874”
specificityas written: “Specificity (PRL)”0.989
source quote (p.15)
“VDA caries had a standalone specificity of 0.867 for caries' and 0.989 for PRL' second operating points respectively.”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
-100%
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-09-02.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Related FDA clearances

These are recent clearances in the same FDA product-code category. Shared classification does not by itself make a device an appropriate predicate.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K251002