Clarius OB AI

K233955

Clarius Mobile Health Corp. · cleared 2024-06-14 · product code IYN · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“Clarius OB Al is a machine learning algorithm that is incorporated into the Clarius App software as part of the complete Clarius Ultrasound Scanner system for use in obstetric (OB) ultrasound imaging applications.”
Algorithmdeep learning image segmentation algorithm; deep neural network (DNN) model
source quote (p.6)
“Clarius OB Al is intended for use by trained healthcare practitioners for non-invasive measurements of fetal biometric parameters on ultrasound data acquired by the Clarius Ultrasound Scanner system (i.e., curvilinear scanner) using a deep learning image segmentation algorithm. The Clarius OB Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing.”
Adaptive (vs locked)No
source quote (p.9)
“Ultrasound image processing software application implementing artificial intelligence utilizing non-adaptive machine learning algorithms trained with clinical and/or artificial data intended for”
PCCPYes
source quote (p.1)
“FDA's substantial equivalence determination also included the review and clearance of your Predetermined Change Control Plan (PCCP).”
Cybersecurity addressedYes
source quote (p.11)
“Clarius conforms to the cybersecurity requirements by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed or transferred from a medical device to an external recipient.”

Validation studies (1)

Retrospective clinical

n=347 patients · 25 site(s)

endpoints: verify that Clarius OB Al fetal biometric measurements (i.e., CRL, BPD, HC, AC, and FL) are non-inferior to manual measurements performed by expert clinicians; verify a high correlation between fetal gestational age calculated using manual expert measurements and Clarius OB Al biometric measurements

standards: IEC 62304:2006 + A1:2015 - Medical device software - Software life cycle processes, ISO 14971:2019 Medical devices Application of risk management to medical devices, NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set, IEC 62366-1:2015 + A1:2020 Medical devices Part 1: Application of usability engineering to medical devices, ISO 15223-1:2021 Medical devices Symbols to be used with medical device labels, labelling and information to be supplied

Reported performance (3 observations)

agreement_kappaas written: “Intraclass Correlation Coefficient (ICC)”0.99CI 0.994—0.997
source quote (p.13)
“ICC across all fetal biometrics between Clarius OB Al and the reviewers was calculated to be 0.99 (95% CI 0.994—0.997).”
iouas written: “Average Jaccard scores (range)”stated without valueCI 0.73 (95% CI 0.72--0.74) to 0.94 (95% CI 0.93--0.94)
source quote (p.13)
“The range of the average Jaccard scores (for all anatomical structures) between Clarius OB Al and the reviewers was 0.73 (95% CI 0.72--0.74) to 0.94 (95% CI 0.93--0.94)”
diceas written: “Average Dice scores (range)”stated without valueCI 0.84 (95% CI 0.83--0.87) to 0.97 (95% CI 0.96--0.97)
source quote (p.13)
“and the range of the average dice scores (for all anatomical structures) between Clarius OB Al and the reviewers was 0.84 (95% CI 0.83--0.87) to 0.97 (95% CI 0.96--0.97).”

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

85
recalls in product code, 24mo
554
MAUDE reports in code, 12mo
+85%
vs code's own 3-yr baseline
7
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K253593 (decision 2026-03-02) from Clarius Mobile Health Corp. for a matching device line ("Clarius Ejection Fraction AI") — a new clearance for the same line is a change event. The newer clearance's parsed summary mentions a PCCP.

    first seen 2026-07-08 · k_number:K253593

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K250226 (decision 2025-05-08) from Clarius Mobile Health Corp. for a matching device line ("Clarius Median Nerve AI") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K250226

  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K243853 (decision 2025-04-16) from Clarius Mobile Health Corp. for a matching device line ("Clarius Prostate AI") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K243853

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (Philips Ultrasound, LLC, initiated 2025-10-31): "Ultrasound system compatibility issues with Apple devices running iOS 18 may cause a failure to perform live imagining." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97843

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (GE Medical Systems, LLC, initiated 2025-09-18): "The Ultrasound-Guided Attenuation Parameter (UGAP) measurement data may display inaccurate values representing liver steatosis. This could potentially lead to inappropriate clinica" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97726

  • recall_reason_pattern

    Software/algorithm-related recall in product code IYN (GE Medical Systems China Co., Ltd. Dev. Zone National Hi-Tech; No., initiated 2025-05-16): "GE HealthCare has become aware that the Estimated Fetal Weight (EFW) measurement data feature on the Versana Premier R3 and LOGIQ F R3 series ultrasound systems can display previou" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:96992

  • …and 1 more.

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/K233955