# K200921: qER

- Pathway: 510(k) (Traditional)
- Applicant: Qure.Ai Technologies
- Decided: Jun 17, 2020 after 72 days
- Product code: QAS (Radiological Computer-Assisted Triage And Notification Software)
- Device class: 2
- Regulation: 21 CFR 892.2080
- Recalls of this device: none
- Data: FDA decisions to Oct 25, 2026; recalls to Oct 12, 2026

## Lineage
Longest line of descent: 2 generations back to DEN170073 (2018). 2 ancestors in all.
1 later device descends from it; 1 cites it directly.
0 of 4 devices in its family (counting itself) have a Class I recall.

## Predicates on the family tree (from the FDA summary)
- K180647: BriefCase, Aidoc Medical, Ltd. (2018) Summary page 4.

## Most influential descendants
- K241923: EFAI Neurosuite CT Midline Shift Assessment System (MLS-CT-100) (2024), 0 descendants of its own

## Indications for use
qER is a radiological computer aided triage and notification software indicated for use in the analysis of non-contrast head CT images. The device is intended to assist hospital networks and trained medical specialists in workflow triage by flagging the following suspected positive findings of pathologies in head CT images: intracranial hemorrhage, mass effect, midline shift and cranial fracture. qER uses an artificial intelligence algorithm to analyze images on a standalone cloud-based application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected findings. Notifications include non-diagnostic preview images that are meant for informational purposes only. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of the device are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.

Source page: https://510kreport.com/device/K200921
Methodology: https://510kreport.com/methodology