BriefCase-Quantification
K241112Aidoc Medical, Ltd. · cleared 2024-05-15 · product code QIH · Radiology
Premarket evidence — what FDA accepted
source quote (p.4)
“The software consists of a single module based on an algorithm programmed component and is intended to run on a linux-based server in a cloud environment.”
source quote (p.5)
“Both devices are artificial intelligence, deep-learning algorithms incorporating software packages for use with compliant scanners, PACS, and radiology workstations.”
source quote (p.5)
“The main difference between the subject and predicate device is the performance, due to its training on a larger data set, in that the subject device demonstrates improved performance over the predicate device.”
Validation studies (1)
Retrospective clinical
n=162 cases · 6 site(s)
endpoints: mean absolute error between the ground truth measurement and algorithm
Reported performance (0 observations)
FDA source did not state a quantitative performance metric — non-reporting is itself the signal.
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
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K242203 (decision 2024-11-22) from Aidoc Medical, Ltd. for a matching device line ("BriefCase-Quantification") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K242203
Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). 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).