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The Press-fit Flared Shell is intended for treatment of patients who are candidates for total hip arthroplasty because the natural femoral head and neck and/or acetabulum have been affected by osteoarthritis, inflammatory arthritis, traumatic arthritis, rheumatoid arthritis, avascular necrosis or femoral neck fracture, and revision arthroplasty where bone loss is minimal. These devices are intended to aid the surgeon in relieving the patient of hip pain and restoring hip motion.

The metal shell is fabricated from wrought/forged or cast Ti-6A1-4V. The outside surface of the shell is textured to provide a roughened surface for enhanced pressfit fixation.

The metal shell is hemispherical in shape and is available with. The screw holes are for the use of 6.5 mm cancellous bone screws for secondary fixation.

The poly liners are manufactured from ultra high molecular weight polyethylene and are available in a neutral and 10° hooded design. The hooded design is intended for those patients prone to subluxation because of soft tissue laxity.

This document is a 510(k) summary for a medical device (Press-fit Flared Shell, a hip replacement component) and does not contain the type of AI/ML or diagnostic study information requested in your prompt.

The prompt asks for details about "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of AI/ML evaluations (e.g., sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance). This K960633 summary describes a traditional orthopedic implant and its mechanical testing.

Therefore, I cannot extract the requested information from the provided text. The document focuses on:

• Device Description: Materials, shape, features.
• Intended Use: Patient conditions for total hip arthroplasty.
• Comparable Features to Predicate Device(s): How it's similar to existing devices.
• Test Results: Briefly mentions "porous attachment strength of liners to shell" and states "All results are sufficient for in-vivo loading."

There is no mention of:

• Acceptance criteria for diagnostic performance metrics (e.g., sensitivity, specificity, AUC)
• Any form of AI/ML algorithm or diagnostic study
• Human readers, expert ground truth, or adjudication
• Training or test sets for an AI model

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