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The GeniCon Pnutemo - Needle is intended for percutaneous insertion into the peritoneal cavity for the purspose of insufflation with carbon dioxide to establish pneumoperitoneum prior to the placement of trocars during laparoscopic procedures.

The GeniCon, Pneumo-Needle is a sterile, disposable Veress needle which is available in 120mm length. The device is equipped with a spring-loaded, round-tipped obturator. In addition, there is a "slide switch" which permits easy ON-OFF control of the gas flow. The most proximal end contains a malue luer lock connector for secure CO2 gas line connection.

The provided text describes a 510(k) premarket notification for the GeniCon Pneumo-Needle. This device is a sterile, disposable Veress needle intended for insufflation with carbon dioxide to establish pneumoperitoneum during laparoscopic procedures. The documentation focuses on demonstrating substantial equivalence to a predicate device and outlines performance tests conducted, but it does not include a study or detailed acceptance criteria for an AI/CADe device.

Therefore, I cannot provide the requested information about acceptance criteria for an AI/CADe device, a study proving it meets acceptance criteria, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or training set details as this information is not present in the provided text.

The "Performance" section explicitly states:

Performance:
A series performance tests were performed on the GeniCon Pneumo-Needle to inspect such areas as:

• Tip Pull Test
• Switch Operation
• Spring Obturator Operation
• Needle Puncture Force Test

These are mechanical performance tests for a physical medical device, not a study evaluating algorithm performance or clinical effectiveness in the context of AI/CADe.

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The AMR Insufflation Needle is a disposable device indicated for use for insufflating the peritoneum prior to laparoscopic surgery.

The design consists of a 14 gauge stainless steel needle attached to a plastic handle. The Insufflation Needle features a spring loaded safety stylet. The position of the safety stylet may be determined external to the patient by a color coded indicator on the handle. The needle will be made in two lengths, 120 and 150mm and contains a stopcock with a luer port for connection to an insufflation pump.

This 510(k) summary for the K963359 Applied Medical Insufflation Needle does not contain any information about acceptance criteria or a study proving device performance in the context of an AI/ML-driven device.

The document describes a medical device, an insufflation needle, which is a physical instrument, not a software algorithm. Therefore, the questions you've posed, which are specifically tailored for AI/ML device validation, are not applicable to the provided text.

Here's why each of your requested points cannot be answered from the provided input:

1. A table of acceptance criteria and the reported device performance: Not applicable. The document mentions "Mechanical testing was conducted to verify the safety and functional performance," but it does not specify quantitative acceptance criteria (e.g., minimum tensile strength, maximum leakage rate) or report specific performance values against them.
2. Sample size used for the test set and the data provenance: Not applicable. This refers to data used for AI/ML model validation. The insufflation needle uses mechanical testing, not data sets in this context.
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 AI/ML model. Mechanical testing of a physical device doesn't involve "experts establishing ground truth" in this sense.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. This is for expert consensus in AI/ML.
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 relates specifically to the impact of AI on human performance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a physical needle, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. "Ground truth" in this context would likely be engineering specifications or measurements (e.g., burst pressure, flow rate), not expert consensus or pathology.
8. The sample size for the training set: Not applicable. There is no AI/ML model being trained.
9. How the ground truth for the training set was established: Not applicable. No AI/ML model.

In summary, the provided document describes a traditional medical device and its predicate comparison, not an AI/ML device. Therefore, the questions are misaligned with the content.

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