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510(k) Data Aggregation

    K Number
    K162008

    Validate with FDA (Live)

    Device Name
    JiveX
    Date Cleared
    2016-09-16

    (58 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    JiveX is a software only Picture Archiving and Communication System intended to display, process, read, report, communicate, distribute, store, and archive medical data which is available as DICOM or HL7 data, including mammographic images, and bio signals. JiveX also converts case related non-image documents, archives them as DICOM data and serves as a vendor neutral archive.

    It supports the physician in diagnosis.

    For primary image diagnosis in Mammography only uncompressed images must be used. Also monitors (displays) and printers which received FDA clearance for Mammography must be used.

    Note: Web-based image distribution and mobile device display are not intended for diagnostic purposes.

    Device Description

    JiveX is a software only Picture Archiving and Communication System intended to display, process, read, report, communicate, distribute, store, and archive medical data which is available as DICOM or HL7 data, including mammographic images, and bio signals. JiveX also converts case related non-image documents, archives them as DICOM data and serves as a vendor neutral archive.

    It supports the physician in diagnosis.

    For primary image diagnosis in Mammography only uncompressed or non-lossy compressed images must be used. Also monitors (displays) and printers which received FDA clearance for Mammography must be used.

    A Communication Server is communicating, storing, and archiving DICOM data and also renders images for the web based image distribution.

    Fat clients, rich in rendering and image manipulation functionality, are medical diagnostic and viewing workplaces. When using FDA cleared monitors diagnosis on digital mammography images is possible.

    The web based clients are intended for image distribution on either personal computers or mobile devices.

    JiveX is a client server solution that is mainly implemented in Java. Clients run on personal computers with MS windows operating systems. The mobile client runs on iPAD. The server also runs on MS Windows operating systems using server hardware either directly or via virtual machines.

    JiveX is a software only medical device.

    AI/ML Overview

    The provided text is a 510(k) Summary for the JiveX Picture Archiving and Communication System (PACS). It compares JiveX 5.0 to a predicate device, JiveX 4.7. However, it does not contain information about specific acceptance criteria, device performance metrics, or a study reporting those metrics to prove the device meets acceptance criteria.

    Instead, the document focuses on demonstrating substantial equivalence to a predicate device by comparing intended use, technological characteristics, and a feature set. It describes software development and testing processes but does not present quantitative performance data.

    Therefore, I cannot fulfill your request for:

    1. A table of acceptance criteria and reported device performance.
    2. Sample size used for the test set and data provenance.
    3. Number of experts and qualifications for ground truth.
    4. Adjudication method for the test set.
    5. MRMC comparative effectiveness study or related effect size.
    6. Standalone performance study for the algorithm.
    7. Type of ground truth used.
    8. Sample size for the training set.
    9. How ground truth for the training set was established.

    This type of information is typically required for AI/ML-driven medical devices that make diagnostic classifications or predictions, which is not the primary function of a PACS system like JiveX according to this document. JiveX is a system for displaying, processing, storing, and archiving medical data, supporting the physician in diagnosis, rather than performing it autonomously. Its software validation focuses on functionality, reliability, and safety in handling and presenting medical data, not on diagnostic accuracy of an AI model within the PACS.

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