EyeArt

K200667

Eyenuk, Inc · cleared 2020-08-03 · product code PIB · Ophthalmic

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“EyeArt is a software as a medical device that consists of several components – Client, Server, and Analysis Computation Engine – as presented in Figure 1 below.”
Algorithmensemble of clinically aligned machine learning (deep learning) algorithms
source quote (p.6)
“It consists of an ensemble of clinically aligned machine learning (deep learning) algorithms.”
Adaptive (vs locked)FDA source did not state this
PCCPYes
source quote (p.6)
“A change protocol was also submitted, to allow for updates and improvements to EyeArt while ensuring that the changes do not introduce risks that adversely affect the safety and effectiveness of the device for its intended use.”
Cybersecurity addressedYes
source quote (p.6)
“EyeArt also implements comprehensive cybersecurity measures for data confidentiality, data integrity, and data and service availability. Designed to meet industry standard cybersecurity best practices, EyeArt ensures that data remains secure (with encryption during transit and at rest) and private (with authentication and authorization protocols enabling access).”

Validation studies (2)

Prospective clinical

n=655 patients · 11 site(s)

endpoints: sensitivity and specificity of EyeArt for detecting mtmDR and vtDR in subject eyes

Reader study (MRMC)

n=62 patients · 2 site(s)

endpoints: Repeatability (intra-operator variability); Reproducibility (inter-operator variability)

Reported performance (4 observations)

sensitivity0.929CI [87.1% - 97.5%]
source quote (p.19)
“92.9% [87.1% - 97.5%]”
specificity0.856CI [82.2% - 89.1%]
source quote (p.19)
“85.6% [82.2% - 89.1%]”
ppvas written: “Positive Predictive Value (PPV)”0.544CI [45.3% - 63.6%]
source quote (p.19)
“54.4% [45.3% - 63.6%]”
npvas written: “Negative Predictive Value (NPV)”0.985CI [97.3% - 99.5%]
source quote (p.19)
“98.5% [97.3% - 99.5%]”

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
—
vs code's own 3-yr baseline
1
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K223357 (decision 2023-06-16) from Eyenuk, Inc. for a matching device line ("EyeArt v2.2.0") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K223357

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 2026-07-08.

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 Ophthalmic 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.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K200667