qER

K200921

Qure.ai Technologies · cleared 2020-06-17 · product code QAS · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“Qure.ai Head CT scan interpretation software, qER, is a deep-learning-based software device that analyses head CT scans for signs of intracranial hemorrhage, midline shift, mass effect or cranial fractures in order to prioritize them for clinical review. The standalone software device consists of an on-premise module and a cloud module.”
Algorithmdeep-learning-based software device; pre-trained convolutional neural network (CNN)
source quote (p.4)
“Qure.ai Head CT scan interpretation software, qER, is a deep-learning-based software device that analyses head CT scans for signs of intracranial hemorrhage, midline shift, mass effect or cranial fractures in order to prioritize them for clinical review. The standalone software device consists of an on-premise module and a cloud module. The deep learning analysis module underlying qER consists of a set of 4 independent algorithms. The core component of each algorithm is a pre-trained convolutional neural network (CNN) that has been trained to detect a specific abnormality from head CT scan images.”
Adaptive (vs locked)No
source quote (p.5)
“A predefined threshold is applied to each of the 4 scan-level outputs, to determine the presence (positive, 1) or absence (negative, 0) of the abnormality for purposes of triage for further review. Both devices also consist of a module that performs the analysis using a pre-trained artificial intelligence algorithm.”
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Retrospective clinical

n=1,320 scans

endpoints: accuracy of qER at triaging head CT scans; clinical benefit of such triage

Reported performance (8 observations)

sensitivity0.9853CI 97.45 - 99.24
source quote (p.10)
“Any of the 4 target abnormalities 98.53 (97.45 - 99.24), 807/819”
specificity0.9122CI 88.39 - 93.55
source quote (p.10)
“Any of the 4 target abnormalities ... 91.22 (88.39 - 93.55), 457/501”
aurocas written: “AUC (Intracranial Hemorrhage)”0.9853CI 98.00 - 99.15
source quote (p.10)
“Intracranial Hemorrhage 98.53 (98.00 - 99.15)”
aurocas written: “AUC (Cranial Fracture)”0.9766CI 96.88 - 98.57
source quote (p.10)
“Cranial Fracture 97.66 (96.88 - 98.57)”
aurocas written: “AUC (Mass Effect)”0.9909CI 98.73 - 99.52
source quote (p.10)
“Mass Effect 99.09 (98.73 - 99.52)”
aurocas written: “AUC (Midline Shift)”0.9909CI 98.74 - 99.51
source quote (p.10)
“Midline Shift 99.09 (98.74 - 99.51)”
time_to_resultas written: “Mean Time to open exam in the standard of care”65.54CI 59.14 – 71.76
source quote (p.11)
“Time to open exam in the standard of care 65.54 (59.14 - 71.76)”
time_to_resultas written: “Mean Time-to-notification with qER”2.11CI 1.45 - 2.61
source quote (p.11)
“Time-to-notification with qER 2.11 (1.45 - 2.61)”

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
2
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K251610 (decision 2025-09-08) from Qure.ai Technologies for a matching device line ("qER-CTA (v1.0)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K251610

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K211222 (decision 2021-07-30) from Qure.ai Technologies for a matching device line ("qER-Quant") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K211222

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/K200921