DeepTek CXR Analyzer v1.0

K231001

DeepTek Medical Imaging Pvt Ltd · cleared 2023-10-05 · product code MYN · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“DeepTek CXR Analyzer v1.0 is a computer-assisted detection (CADe) software device”
AlgorithmArtificial Neural Networks
source quote (p.7)
“Artificial Neural Networks”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.7)
“Additionally, the software validation activities were performed in accordance with IEC 62304 Edition 1.1 2015-06 Medical device software – Software life cycle processes, in addition to the FDA Guidance documents, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices” and “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions””

Validation studies (2)

Standalone

n=3,000 images · 13 site(s)

endpoints: detection (by measuring sensitivity, specificity, and AUROC); localization (by measuring wAFROC-FOM) of suspicious ROIs

Reader study (MRMC)

n=300 images · 13 site(s)

endpoints: determine whether the performance of readers aided by DeepTek CXR Analyzer is superior to their performance when unaided by DeepTek CXR Analyzer, as determined by the wAFROC-FOM score.

standards: FDA's guidance document for industry and FDA staff titled “Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device Data in Premarket Notification (510(k)) Submissions”

Reported performance (7 observations)

sensitivity0.926CI [0.917-0.933]
source quote (p.9)
“Aggregate 0.926 [0.917-0.933]”
specificity0.933CI [0.925-0.938]
source quote (p.9)
“Aggregate 0.933 [0.925-0.938]”
aurocas written: “auc”0.974CI [0.970-0.977]
source quote (p.9)
“Aggregate 0.974 [0.970-0.977]”
sensitivityas written: “Sensitivity (Aided Readers)”0.886CI [0.813-0.945]
source quote (p.12)
“Aggregate 0.886 [0.813-0.945]”
sensitivityas written: “Sensitivity (Unaided Readers)”0.81CI [0.699-0.902]
source quote (p.12)
“Aggregate 0.810 [0.699-0.902]”
specificityas written: “Specificity (Aided Readers)”0.949CI [0.884-0.990]
source quote (p.12)
“Aggregate 0.949 [0.884-0.990]”
specificityas written: “Specificity (Unaided Readers)”0.911CI [0.804-0.972]
source quote (p.12)
“Aggregate 0.911 [0.804-0.972]”

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
-100%
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/K231001