Automated Aortic Stenosis Software (AutoAS)

K254161

GE Medical Systems Ultrasound & Primary Care Diagnostics, LLC · cleared 2026-03-27 · product code POK · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“AutoAS is a software application intended to assist medical professionals in the assessment of moderate/severe aortic stenosis (AS).”

Algorithmdeep-learning artificial intelligence

source quote (p.14)

“Both devices utilize deep-learning artificial intelligence as the core technology to provide diagnostic aid to the user in the assessment of heart conditions.”

Adaptive (vs locked)FDA source did not state this

PCCPFDA source did not state this

Cybersecurity addressedYes

source quote (p.7)

“Software documentation generated as part of the design process included: ... Cybersecurity”

Validation studies (2)

Standalone

n=401 patients · 4 site(s)

endpoints: Area Under the ROC Curve; Specificity; Sensitivity

Reader study (MRMC)

n=220 patients · 3 site(s)

endpoints: sensitivity; specificity; partial AUROC; inter-rater agreement

Reported performance (6 observations)

sensitivity75.2CI 67.4% - 83.0%

source quote (p.9)

“Specificity of 92.4% [95% CI: 86.3% - 98.4%] and sensitivity of 75.2% [95% CI: 67.4% - 83.0%] were observed, on par with original reading cardiologists when compared to the same reference panel).”

specificity92.4CI 86.3% - 98.4%

source quote (p.9)

“Specificity of 92.4% [95% CI: 86.3% - 98.4%] and sensitivity of 75.2% [95% CI: 67.4% - 83.0%] were observed, on par with original reading cardiologists when compared to the same reference panel).”

aurocas written: “auc”93.2CI 90.5% - 95.6%

source quote (p.9)

“The standalone assessment findings demonstrated strong overall performance; Area Under the ROC Curve, 93.2% [95% CI: 90.5% - 95.6%] which is statistically significantly greater than the predefined performance target.”

sensitivityas written: “Sensitivity improvement (Aided vs. Unaided)”5.5CI 1.5%, 9.5%

source quote (p.11)

“A statistically significant improvement in sensitivity was observed for the “Aided” readers compared to the “Unaided” readers (+ 5.5%, 95% CI: (1.5%, 9.5%))”

aurocas written: “Difference in partial AUROC”8.9CI 1.2%, 20.5%

source quote (p.11)

“the critical region of the ROC curve revealed superiority for the “Aided” group with an 8.9% [95% CI: 1.2%, 20.5%] difference in partial AUROC.”

agreement_kappaas written: “Inter-rater agreement (Aided)”89

source quote (p.11)

“In addition, aided readers demonstrated higher inter-rater agreement (89.0%) than unaided readers (81.9%), comparable to the reference standard (88.7%), reflecting improved reader consistency and diagnostic performance.”

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

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

drift signals on this device

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).