Annalise Enterprise
K253818Harrison-AI Medical Pty, Ltd. · cleared 2026-03-03 · product code QAS · Radiology
Premarket evidence — what FDA accepted
source quote (p.23)
“The subject device and the predicate device are both software only packages, devices intended to assist with worklist triage by providing notification of findings.”
source quote (p.7)
“Radiological findings are identified by the device using an AI algorithm – a convolutional neural network trained using deep-learning techniques.”
source quote (p.22)
“FDA Guidance: Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions”
Validation studies (2)
Standalone
n=977 cases · 5 site(s)
endpoints: AUC; Sensitivity; Specificity
standards: ISO 13485, ISO 14971, IEC 62304, IEC 62366-1, AAMI TIR 57, ISO/IEC 27001, IEC 82304-1
Bench
n=277 cases
endpoints: triage turn-around time
Reported performance (4 observations)
source quote (p.20)
“89.2 (85.8,92.6)”
source quote (p.20)
“84.1 (81.5,86.9)”
source quote (p.19)
“0.952 (0.937, 0.965)”
source quote (p.20)
“The results demonstrated a triage turn-around time of 81.6 (95% CI: 80.3 – 82.9) seconds”
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
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).