CogNet AI-MT+

K252482

Medcognetics, Inc. · cleared 2025-12-11 · product code QFM · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“The MedCognetics CogNet AI-MT+ is a non-invasive computer-assisted triage and notification software as a medical device (SaMD) that analyzes DBT screening mammograms using a machine learning algorithm and notifies a PACS/workstation of the presence of findings suspicious of cancer in a study.”
Algorithmmachine learning algorithm, Deep Learning techniques
source quote (p.5)
“The MedCognetics CogNet AI-MT+ is a non-invasive computer-assisted triage and notification software as a medical device (SaMD) that analyzes DBT screening mammograms using a machine learning algorithm and notifies a PACS/workstation of the presence of findings suspicious of cancer in a study.This module accepts the normalized image data from the pre-processing module and uses Deep Learning techniques to extract features to determine if any lesions suspicious for cancer exist in the mammogram study”
Adaptive (vs locked)No
source quote (p.11)
“This process is repeated for a fixed number of iterations, over which time the model's AUROC on both the training and development datasets are monitored to ensure that the model is not overfitting.”
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.7)
“MedCognetics is attentive to cybersecurity issues in medical devices. CogNet AI- MT+ is HIPAA compliant and assures that Personal Health Information is protected by promoting anonymization of data prior to analysis. This is accomplished by requiring de-identification as part of the data transfer to the CogNet AI-MT+ algorithm. DICOM data retains the necessary DICOM tags using these to merge the secondary capture image containing the CogNet analysis results into the original mammogram study for final viewing by a MQSA interpreting physician. DICOM data in network and in transfer to the CogNet AI- MT+ algorithm is encrypted in transit and at rest. User access is strictly password protected. The transferred data is subject to existing firewall solutions, auditing, and all interactions are logged to facilitate review of potential issues.”

Validation studies (1)

Retrospective clinical

n=806 patients

endpoints: Area Under Receiver Operating Characteristics (AUROC); sensitivity; specificity

standards: IEC 62304, 21 CFR Part 820, DICOM PS3.1

Reported performance (3 observations)

sensitivity0.8809CI 0.8511 - 0.9032
source quote (p.12)
“Sensitivity = 0.8809 (95% CI: 0.8511 - 0.9032)”
specificity0.9156CI 0.8933 - 0.9380
source quote (p.12)
“Specificity = 0.9156 (95% CI: 0.8933 - 0.9380)”
aurocas written: “auc”0.9548CI 0.9364 - 0.9699
source quote (p.12)
“AUROC = 0.9548 (95% CI: 0.9364 - 0.9699)”

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
0
drift signals on this device

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/K252482