Sonix Health
K230209Ontact Health Co., Ltd. · cleared 2023-10-20 · product code QIH · Radiology
Premarket evidence — what FDA accepted
source quote (p.5)
“Sonix Health will be offered as SW only, to be installed directly on customer PC hardware. Sonix Health is DICOM compliant and is used within a local network.”
source quote (p.5)
“Sonix Health utilizes a two-step algorithm. A single identification model identifies a view in the first step. The second step performs the deep learning algorithm according to the view. The deep learning algorithms for the second step are categorized as B-mode, M-mode, and Doppler algorithms. The main algorithm of Sonix Health is to identify the view and segment the anatomy in the image.”
source quote (p.9)
“Throughout the verification and validation process, traceability was maintained, encompassing risk management (including Cyber Security and Usability).”
Validation studies (1)
Retrospective clinical
n=2,744 images · 2 site(s)
endpoints: left ventricle ejection fraction (LVEF); accuracy for view recognition; correlation coefficient when compared to manual measurements
standards: Digital Imaging and Communications in Medicine (DICOM) Set (Ps3.1 - .20), IEC 62304:2006, Medical Device Software - Software Life Cycle Processes., ISO 14971 Second edition 2007-03-01, Medical devices - Application of risk management to medical devices., IEC 62366-1 Edition 1.1 2020-06, Medical devices-Part 1 Application of usability engineering to medical devices.
Reported performance (1 observation)
source quote (p.9)
“Sonix Health passed the test in two categories: an average accuracy of 98.22% for view recognition”
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
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K240645 (decision 2024-11-27) from Ontact Health Co., Ltd for a matching device line ("Sonix Health") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K240645
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).