DeepTek CXR Analyzer v1.0
K231001DeepTek Medical Imaging Pvt Ltd · cleared 2023-10-05 · product code MYN · Radiology
Premarket evidence — what FDA accepted
source quote (p.3)
“DeepTek CXR Analyzer v1.0 is a computer-assisted detection (CADe) software device that analyzes chest radiograph studies using machine learning techniques to identify, categorize, and highlight suspicious ROIs in one of the following categories: Lungs, Pleura, Cardiac, and Hardware.”
source quote (p.5)
“DeepTek CXR Analyzer detects suspicious ROIs by analyzing adult frontal chest radiographs using deep learning algorithms and provides relevant annotations to assist radiologists with their interpretations.”
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 scans · 13 site(s)
endpoints: evaluate the performance of DeepTek CXR Analyzer software device in detection (by measuring sensitivity, specificity, and AUROC) and localization (by measuring wAFROC-FOM) of suspicious ROIs from chest X-rays and classifying each ROI into one of the following four categories: Lungs, Pleura, Cardiac, or Hardware.
Retrospective clinical
n=300 images · 13 site(s)
endpoints: determine the impact of the DeepTek CXR Analyzer on reader performance in detecting and localizing suspicious ROIs in chest radiographs; 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 (3 observations)
source quote (p.9)
“Aggregate 0.926 [0.917-0.933]”
source quote (p.9)
“Aggregate 0.933 [0.925-0.938]”
source quote (p.9)
“Aggregate 0.974 [0.970-0.977]”
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).