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The Crystalsert Delivery System is intended to be used to fold and deliver the Crystalens accommodating intraocular lens and other intraocular lenses identifying the Crystalsert delivery system in their approved labeling.

The Crystalsert Delivery System is a sterile, single-use device used to fold and insert an intraocular lens through surgical procedure into a human eye. The system provides a tubular pathway through an incision over the iris, allowing delivery of an IOL into the capsular bag.

The provided document describes the Bausch & Lomb Crystalsert Delivery System, a device for inserting intraocular lenses. However, it does not contain a study to prove the device meets acceptance criteria in the context of an AI/ML algorithm or a typical clinical trial with acceptance criteria for performance metrics like sensitivity, specificity, or accuracy.

Instead, this 510(k) submission focuses on demonstrating substantial equivalence to a predicate device through comparative analysis and functional testing against an international standard.

Therefore, I cannot fulfill all parts of your request as the information is not present in the provided text. I will address the parts that are relevant to this type of device submission.

Here's the breakdown of what can be extracted from the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

This document does not present acceptance criteria or reported performance in the typical format of a study for an AI/ML device (e.g., sensitivity, specificity thresholds). Instead, safety and effectiveness are established through demonstrating equivalence to a predicate device and conformance to an international standard.

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

Not applicable for this type of device submission. This is a medical device for IOL insertion, not an AI/ML algorithm evaluated on a data set. The "test set" would be the functional testing of the device itself (e.g., number of units tested during engineering verification), which is not explicitly stated but implied by the "successful functional testing" claim. Data provenance like country of origin or retrospective/prospective is not relevant here.

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

Not applicable. Ground truth for an AI/ML algorithm is not relevant. The "ground truth" for this device would be its ability to correctly fold and insert an IOL, which is assessed via engineering and performance testing against a standard. Experts would be engineers and quality control personnel.

4. Adjudication method for the test set

Not applicable. Adjudication methods (e.g., 2+1) are for human interpretation of data for AI/ML algorithm training/testing. This device relies on objective functional testing against a standard.

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 not an AI-assisted diagnostic or prognostic device for human readers.

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

Not applicable. This device is a manual tool, not an algorithm.

7. The type of ground truth used

For this device, the "ground truth" is established by conformance to an international standard (ISO 11979-3, section 5) and successful functional performance specifications for its intended use (folding and inserting an IOL without damage). This is validated through engineering and performance testing.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that requires a training set.

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

Not applicable.

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