uAI Easy Triage ICH

K242292

Shanghai United Imaging Intelligence Co., Ltd. · cleared 2024-09-24 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“uAI Easy Triage ICH is a radiological computer-assisted triage and notification software device indicated for analysis of non-enhanced head CT images.”
Algorithmartificial intelligence CNN (convolutional neural networks) and advanced image processing
source quote (p.6)
“The uAI Easy Triage ICH algorithm uses artificial intelligence CNN (convolutional neural networks) and advanced image processing to triage the non-contrast CT images for suspicious intracranial hemorrhage.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.14)
“Those documentations include: ... Cybersecurity Documents. Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions (Document issued on September 27, 2023).”

Validation studies (1)

Retrospective clinical

n=295 cases

endpoints: sensitivity; specificity; time to notification

standards: NEMA PS 3.1 - 3.20 Digital Imaging and Communications in Medicine (DICOM) Set, ISO 14971 Medical devices – Application of risk management to medical devices (Third Edition 2019-12), IEC 62304 Medical device software - Software life cycle processes (Edition 1.1 2015-06 CONSOLIDATED VERSION), Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions (Document issued on September 27, 2023)

Reported performance (3 observations)

sensitivity0.92CI 86%-96%
source quote (p.15)
“Comparing the uAI Easy Triage ICH software output to the ground truth, the sensitivity and specificity of uAI Easy Triage ICH are 92% (95% CI: 86%-96%) and 95% (95% CI: 90%-98%), respectively, exceeding the acceptance criteria of 80%.”
specificity0.95CI 90%-98%
source quote (p.15)
“Comparing the uAI Easy Triage ICH software output to the ground truth, the sensitivity and specificity of uAI Easy Triage ICH are 92% (95% CI: 86%-96%) and 95% (95% CI: 90%-98%), respectively, exceeding the acceptance criteria of 80%.”
time_to_resultas written: “Time to Notification”41.1CI 40.1, 42.1
source quote (p.16)
“The average Time to Notification in seconds was 41.1 with a 95% confidence interval (CI) for the mean equaling (40.1, 42.1).”

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/K242292