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The FemEye Two™ Hysteroscope is used to permit viewing of the cervical canal and uterine cavity for the purpose of performing diagnostic procedures. Generally recognized indications for diagnostic hysteroscopy include:

• Abnormal Uterine Bleeding .
• Infertility and Pregnancy Wastage .
• Evaluation of Abnormal Hysterosalpingogram, ●
• Intrauterine Foreign Body .
• Amenorrhea ●
• Pelvic Pain .

The FemEye Two™ Hysteroscope is designed as a handheld, low-voltage camera device suitable for use during both in-office as well as in-hospital diagnostic procedures. The FemEye Two is a continuous flow hysteroscope intended to permit viewing of the cervical canal and uterine cavity for the purpose of performing diagnostic procedures.
The device consists of a hysteroscopic endoscope and is provided sterile for single patient use. It consists of a small diameter, rigid shaft and a handle. The shaft contains a camera and integrated light source as well as an irrigation/working channel port. The nondisposable portion of the FemEye Two is the battery cartridge which powers the device.

The provided text describes a 510(k) premarket notification for the FemEye Two™ Hysteroscope. It details the device, its intended use, comparison to predicate devices, and supporting data. However, the document does not contain information about acceptance criteria or a study that specifically proves the device meets those criteria in the way typically expected for an AI/algorithm-based medical device.

The studies mentioned are for general medical device safety and functionality, not for performance metrics related to diagnostic accuracy or AI performance. Therefore, I cannot populate the table or answer all of your specific questions related to AI/algorithm performance.

Here's a breakdown of what is available and what is not:

Acceptance Criteria and Reported Device Performance

This information is not provided in the document. The document describes a traditional medical device (hysteroscope), not an AI device with performance metrics like accuracy, sensitivity, or specificity. There are no acceptance criteria for diagnostic performance or AI algorithm output listed.

Study Details (as inferable from the document, with limitations for AI specifics)

The document refers to a "clinical usability study" but does not provide details on its methodology, sample size, or specific performance metrics that would be relevant to an AI model's output. The other studies are for physical device characteristics and safety.

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not specified for any study, particularly not for a diagnostic performance test set.
   • Data Provenance: Not specified.

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

   • Number of Experts: Not specified.
   • Qualifications of Experts: Not specified.

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

   • Not specified.

4. 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:

   • MRMC Study: No, this type of study is not mentioned as having been performed. The device is a hysteroscope for direct viewing, not an AI-assisted diagnostic tool for image analysis.
   • Effect size of human readers with/without AI assistance: Not applicable, as no AI component or related study is described.

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

   • Not applicable, as no AI algorithm is described.

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

   • Not specified, as no diagnostic performance study is detailed.

7. The sample size for the training set:

   • Not applicable, as no AI model or training process is described.

8. How the ground truth for the training set was established:

   • Not applicable, as no AI model or training process is described.

Summary of Supporting Data (as provided in the document):

The document lists the following studies and compliance:

• Biocompatibility Data: Demonstrates compliance with ISO 10993.
• Electrical Safety and Electromagnetic Compatibility Data: Demonstrates compliance with IEC 60601-2-18, IEC 60601-1, and IEC 60601-1-2.
• Bench Testing: Demonstrates compliance with ISO 8600-3 and ISO 8600-5. This included:
  • Tensile Strength test: Joints can withstand a 5.0 lb tensile load.
  • Torque test: Device can withstand a 1 lb-inch torque.
  • Fatigue test: Rotation knob can withstand multiple actuations without affecting image functionality.
  • Flow test: Verified flow of 120 ml per minute without leaks.
• Clinical Usability Study: Results indicate the FemEye Two is "safe and effective when operated by the intended user." No further details on this study (e.g., sample size, specific outcomes, metrics of "effectiveness") are provided.

Conclusion: The provided text describes a traditional hysteroscopic device that is cleared based on mechanical, electrical, biocompatibility, and general usability testing, along with substantial equivalence to predicate devices. It does not involve artificial intelligence or algorithms requiring diagnostic performance metrics or studies as outlined in your questions for AI-based devices.

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