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510(k) Data Aggregation

    K Number
    K031929
    Manufacturer
    Date Cleared
    2003-07-08

    (15 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K023341

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The 5MP TFT LCD Monitor System IF2105A ™ is intended to be used in displaying and viewing medical images for review and analysis by trained medical practitioners.

    Device Description

    The 5MP TFT LCD Monitor System IF2105A™ is a flat panel hi-resolution LCD monitor system for displaying medical images. The system consists of a state-ofthe-art LCD monitor and a high-resolution graphic control board that connects to a PACS workstation for grayscale image display. The WIDE controller board is installed into the PACS workstation computer or other computer system used to display PACS medical images.

    AI/ML Overview

    This 510(k) submission describes a 5MP TFT LCD Monitor System. The document does not contain the kind of detailed information typically found in a study proving a device meets acceptance criteria for an AI/ML product. This is a submission for a medical image display system, which is hardware, not an AI/ML diagnostic or prognostic device.

    Therefore, many of the requested categories (such as sample sizes for test/training sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth types) are not applicable to this type of device.

    Below is a breakdown of the available information based on the provided text, adapted to reflect that this is a hardware medical device rather than an AI/ML algorithm.


    1. Table of Acceptance Criteria and Reported Device Performance

    The submission describes the device (5MP TFT LCD Monitor System IF2105A™) as a flat panel hi-resolution LCD monitor system for displaying medical images. It does not provide specific performance metrics in terms of clinical accuracy or an "algorithm's performance" as one would expect for an AI/ML device. Instead, the acceptance criteria relate to its regulatory classification, technological characteristics, and safety/quality standards.

    Acceptance Criteria CategorySpecific Criteria/StandardReported Device Performance/Compliance
    Regulatory ClassificationDevice Classification Name: SYSTEM, IMAGE PROCESSING, RADIOLOGICAL(Predicate Device) 892.2050 - This device is categorized under the same classification (892.2050).
    Intended UseDisplaying and viewing medical images for review and analysis by trained medical practitioners.The device's stated "Indications for Use" matches this intent.
    Safety and Quality StandardsUL2601-1/EN60601-1 / IEC601-1 (Safety/Immunity), FCC Class B, CE, VCCI, UL 950, cUL2601-1, CE Mark EMC/IEC"The 5MP TFT LCD Monitor System IF2105A ™ will be manufactured by WIDE Corporation in accordance with the voluntary and safety standards..." (lists all mentioned standards).
    Technological CharacteristicsImage display system consisting of computer software and components; does not contact the patient; does not control life-sustaining devices; allows for human intervention.The "Device Description" and "Technological Characteristics" sections confirm these attributes.
    Hazard AnalysisPotential hazards must be classified."The submission contains the results of a hazard analysis and the potential hazards have been classified as Minor."
    Substantial EquivalenceDemonstrates equivalence to a legally marketed predicate device (CORNIS 5MP MEDICAL FLAT PANEL DISPLAY SYSTEM, K023341).FDA determined "the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices..."

    2. Sample size used for the test set and the data provenance

    Not applicable. This is a hardware device. The "testing" involved compliance with electrical safety, EMC, and regulatory standards, rather than clinical performance on a dataset.


    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    Not applicable. This is a hardware device. No clinical "ground truth" was established for performance testing as would be for an AI/ML algorithm. The "experts" involved would be regulatory reviewers, engineers for compliance testing, and the submitter's development team ensuring specifications are met.


    4. Adjudication method for the test set

    Not applicable. This is a hardware device.


    5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

    Not applicable. This is a hardware device. It is a display system, not an AI assistance tool.


    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

    Not applicable. This is a hardware device. There is no algorithm for standalone performance evaluation in the context of an AI/ML diagnostic.


    7. The type of ground truth used

    Not applicable. For a hardware monitor, the "ground truth" would be objective measurements against technical specifications (e.g., luminance, resolution, color accuracy), not pathology or outcomes data. These technical specifications are implicitly evaluated through compliance with standards.


    8. The sample size for the training set

    Not applicable. This is a hardware device. No training set for an AI/ML algorithm is involved.


    9. How the ground truth for the training set was established

    Not applicable. This is a hardware device. No training set for an AI/ML algorithm is involved.

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