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510(k) Data Aggregation

    K Number
    K251209
    Date Cleared
    2025-06-12

    (55 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Medical Monitor (32HS710S)

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

    This medical monitor is intended to provide color video displays and images from medical equipment which include laparoscopy and endoscopy systems for surgery and various medical imaging systems.

    Device Description

    32HS710S LCD monitor is intended to provide color video displays of images from surgical endoscope, laparoscopic camera system and other compatible medical imaging systems. This Medical Monitor has multiple video interface ports such as Display port, HDMI, DVI and SDI. This monitor displays color video and images from medical equipment which include various medical imaging systems. This monitor can be covered over 100% of the sRGB spectrum.

    AI/ML Overview

    The provided FDA 510(k) clearance letter and summary for the Medical Monitor (32HS710S) do not contain information about acceptance criteria or specific studies that prove the device meets such criteria in terms of clinical performance or diagnostic accuracy.

    The document primarily focuses on demonstrating substantial equivalence to a predicate device (K241402) by confirming:

    • Same Indications for Use: The new device is intended for the same purpose as the predicate.
    • Technological Comparison: Differences in specifications (resolution, connectors, power, physical size) are acknowledged but deemed not to affect safety and effectiveness.
    • Non-Clinical Bench Tests: Compliance with electrical safety and electromagnetic compatibility standards (IEC60601-1 Ed 3.2, IEC60601-1-2 Ed 4.1, IEC TR 60601-4-2) is confirmed.
    • Software Validation: The software belongs to "Basic Documentation Level" and was developed and verified/validated according to IEC 62304 and FDA guidance for device software functions.

    Therefore, I cannot extract the requested information (points 1-9) as it pertains to clinical performance, device accuracy, or studies with human readers and ground truth data from this document. This type of information is typically required for devices that perform a diagnostic or analytical function where accuracy metrics like sensitivity, specificity, or reader agreement are critical.

    The Medical Monitor (32HS710S) is a display device. Its "performance" in this context refers to its ability to accurately and safely display images from other medical equipment, not its ability to interpret or diagnose medical conditions. For such a device, the acceptance criteria would focus on technical display characteristics (e.g., color accuracy, resolution, brightness, refresh rate) and safety standards, rather than diagnostic accuracy metrics.

    Here's what can be inferred or stated based on the provided document:

    1. Table of Acceptance Criteria and Reported Device Performance

    Based on the provided document, specific quantitative acceptance criteria related to diagnostic accuracy or clinical performance (e.g., sensitivity, specificity, AUC) and corresponding reported device performance values are NOT available.

    The document refers to compliance with electrical safety and electromagnetic compatibility standards and software validation standards. These are the "acceptance criteria" for this type of device, which is primarily a display unit.

    Acceptance Criterion (Implied/Stated)Reported Device Performance
    Complies with IEC60601-1 Ed 3.2 (General safety and essential performance)Demonstrated compliance through bench tests.
    Complies with IEC60601-1-2 Ed 4.1 (Electromagnetic disturbances)Demonstrated compliance through bench tests.
    Complies with IEC TR 60601-4-2 (Electromagnetic immunity)Demonstrated compliance through bench tests.
    Software designed, developed, verified, and validated according to IEC 62304Software validation report confirms adherence to IEC 62304 and FDA guidance.
    Provides color video displays and images from medical equipmentInherently true based on the device's function as a medical monitor.
    Covers over 100% of the sRGB spectrumStated as a device specification.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    Not applicable / Not provided. The tests described are bench tests for electrical safety and EMC, and software validation. These do not typically involve "test sets" of patient data in the way a diagnostic AI algorithm would.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    Not applicable / Not provided. Ground truth is not established in this context as the device is a monitor, not an interpretive diagnostic tool.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    Not applicable / Not provided.

    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

    No. This type of study is not relevant for a medical display monitor.

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

    No. The device is a display monitor; it does not perform an algorithm-only function that would yield diagnostic output without human interpretation.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    Not applicable / Not provided. The concept of "ground truth" for diagnostic accuracy is not relevant for a display monitor. The "ground truth" for this device would be its ability to accurately display the incoming video signal according to technical specifications.

    8. The sample size for the training set

    Not applicable / Not provided. This information is relevant for AI/ML algorithms that are trained on data, which is not the case for this medical monitor.

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

    Not applicable / Not provided.

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