EFAI NeuroSuite CT ICH Assessment System

K231025

Ever Fortune.AI Co., Ltd. · cleared 2023-10-04 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM (EFAI ICHCT) is a radiological computer-assisted triage and notification software system.”
Algorithmdeep learning algorithms
source quote (p.3)
“EFAI ICHCT analyzes cases using deep learning algorithms to identify suspected ICH findings.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.8)
“Additionally, the software validation activities were performed in accordance with IEC 62304:2006/A1:2016 - Medical device software – Software life cycle processes, in addition to the FDA Guidance documents, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices”(2005), and “Content of Premarket Submission for Management of Cybersecurity in Medical Devices.”

Validation studies (1)

Retrospective clinical

n=288 cases · 23 site(s)

endpoints: the lower bounds of 95% confidence intervals of both sensitivity and specificity should exceed 0.8

standards: IEC 62304:2006/A1:2016 - Medical device software – Software life cycle processes, Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices”(2005), Content of Premarket Submission for Management of Cybersecurity in Medical Devices.

Reported performance (3 observations)

sensitivity0.947CI 0.895-0.974
source quote (p.8)
“The EFAI ICHCT was able to demonstrate sensitivity and specificity of 0.947 (95%CI=0.895-0.974) and 0.949 (95% CI=0.902-0.974) respectively”
specificity0.949CI 0.902-0.974
source quote (p.8)
“The EFAI ICHCT was able to demonstrate sensitivity and specificity of 0.947 (95%CI=0.895-0.974) and 0.949 (95% CI=0.902-0.974) respectively”
aurocas written: “auc”0.983CI 0.969-0.997
source quote (p.8)
“as well as an AUROC of 0.983 (95% CI=0.969-0.997)”

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
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 2026-07-08.

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 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.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K231025