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HylaGuard Moisturizing Cream is intended for the dressing and management of minor skin irritations and minor burns, including sunburn.

HylaGuard Moisturizing Cream is a non-sterile, off-white, low odor, fragrance free, topical device product. HylaGuard Moisturizing Cream forms a semi-permeable, physical barrier that moisturizes and protects skin. HylaGuard Moisturizing Cream is an over-the-counter (OTC) device. The same device has been cleared for prescription use in K150914 under the name of Dash-Topic Plus Cream.

The provided document is a 510(k) premarket notification for a medical device called "HylaGuard Moisturizing Cream." This device is a topical cream intended for the dressing and management of minor skin irritations and minor burns. The document outlines comparisons to a predicate device ("MimyX Cream") to demonstrate substantial equivalence, but it does not describe a study involving AI/ML performance, human readers, or image analysis for detection or diagnosis.

Therefore, I cannot extract the information required to answer your questions about AI/ML acceptance criteria, ground truth establishment, sample sizes for training/test sets, expert adjudication, or MRMC studies. The document describes non-clinical testing related to biocompatibility and stability of a topical cream, not diagnostic performance of an AI/ML system.

The acceptance criteria and study proving the device meets them are related to the cream's physical, chemical, and biological properties, not AI/ML performance.

Here's the relevant information that can be extracted, though it doesn't align with your request for AI/ML-related details:

Device Type: Topical Moisturizing Cream (Drug/Wound Dressing)
Regulatory Pathway: 510(k) Premarket Notification
Demonstration of Safety and Effectiveness: Substantial Equivalence to a predicate device (MimyX Cream) based on similar indications for use, technological characteristics (oil-in-water emulsion with humectant and emollient components), and non-clinical performance data.

Acceptance Criteria and Reported Device Performance (Non-Clinical):

Regarding the other points of your request:

• Sample sized used for the test set and the data provenance: Not applicable. The "test set" here refers to samples of the cream tested for biocompatibility and stability, not a dataset for an AI/ML model.
• Number of experts used to establish the ground truth... and qualifications: Not applicable. Ground truth for a topical cream's biocompatibility is established through standardized laboratory tests, not expert consensus on medical images.
• Adjudication method: Not applicable. No human interpretation or AI/ML output requiring adjudication.
• Multi reader multi case (MRMC) comparative effectiveness study: Not applicable. This study is for a cream, not an AI/ML diagnostic tool.
• Standalone (i.e. algorithm only without human-in-the loop performance): Not applicable. No algorithm is being validated.
• The type of ground truth used: For biocompatibility, the ground truth is the biological response of cells/skin to the material as per ISO standards. For stability, it's the measured physical and chemical properties over time.
• The sample size for the training set: Not applicable. No AI/ML training set.
• How the ground truth for the training set was established: Not applicable.

In summary, the provided document describes a traditional medical device (topical cream) and its non-clinical testing for safety and performance, not an AI/ML-based medical device. Therefore, the questions posed, which are highly specific to AI/ML device validation, cannot be answered from this document.

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