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The CLEVER CHOICE Mini Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by people with diabetes mellitus at home and by health care professionals in clinical settings as an aid in monitoring the effectiveness of diabetes control program. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates.

The alternative site testing in the above system can be used only during steady-state blood glucose conditions.

The system consists of three main products: the meter, test strips, and control solutions. These products have been designed, tested, and proven to work together as a system to produce accurate blood glucose test results. Use only CLEVER CHOICE Mini test strips and CLEVER CHOICE control solutions with the CLEVER CHOICE Mini Blood Glucose Monitoring System.

The provided text is a 510(k) summary for the TaiDoc Technology Corporation's CLEVER CHOICE Mini Blood Glucose Monitoring System. It describes the device, its intended use, and states its substantial equivalence to a predicate device. However, the document does not contain the detailed acceptance criteria or the specific study data that demonstrates the device meets such criteria.

The crucial section (Section 7, "Performance Characteristics") merely states: "CLEVER CHOICE Mini Blood Glucose Monitoring System has the same performance characteristics as the predicate device. A comparison of system performance demonstrated that the CLEVER CHOICE Mini blood glucose monitoring system and the currently marketed FORA G30 Blood Glucose Monitoring System are substantially equivalent. Software verification and validation testing confirmed that the performance, safety and effectiveness of the CLEVER CHOICE Mini blood glucose monitoring system is equivalent to the predicate device."

This indicates that while performance testing was done, the actual criteria and reported results are not included in this summary. The submission relies on demonstrating equivalence to a predicate device (FORA G30 Blood Glucose Monitoring System, K090187) rather than providing a detailed de novo performance study with specific acceptance criteria.

Therefore, I cannot populate the table or answer most of the questions as the information is not present in the provided text.

Here's an attempt to answer what can be inferred or, more importantly, what is missing:

Acceptance Criteria and Device Performance Study Report

1. Table of Acceptance Criteria and Reported Device Performance:

Detailed Study Information (Based on what is and is not in the provided text):

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

• Sample size: Not specified.
• Data provenance: Not specified. Given it's a Taiwanese company, it's possible the data originated from Taiwan, but this is not stated. The type of study (retrospective or prospective) is also not specified.

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

• Not applicable / Not provided. For a blood glucose monitoring system, the "ground truth" (reference method) is typically established by laboratory-grade analyzers (e.g., YSI glucose analyzer) rather than expert consensus on images or interpretations. The document does not specify the reference method used or any experts involved in establishing ground truth.

4. Adjudication method for the test set:

• Not applicable / Not provided. Adjudication methods like 2+1 or 3+1 are typically used in studies involving expert review of medical images or subjective interpretations. For a blood glucose meter, the "truth" is typically determined by an objective, highly accurate reference laboratory method. No such adjudication method is relevant or described for this type of device.

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:

• No. This is a blood glucose monitoring system, not an AI-powered diagnostic imaging device. Therefore, an MRMC study and the concept of "human readers improving with AI assistance" are not applicable.

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

• Not applicable in the AI sense. The device itself is a standalone measurement system. The performance referred to is the accuracy of the glucose measurement by the system (meter + strip). It's an "algorithm only" in the sense that the device outputs a numerical result without human interpretation of the measurement process itself, but it's not an AI algorithm determining a diagnosis or interpreting images. The closest information is that "Software verification and validation testing confirmed that the performance, safety and effectiveness...".

7. The type of ground truth used:

• Not specified. For blood glucose meters, the ground truth is typically a highly accurate laboratory reference method (e.g., a YSI analyzer measuring plasma glucose), but this document does not explicitly state the reference method used in the performance comparison.

8. The sample size for the training set:

• Not applicable / Not provided. This device is based on electrochemical biosensor technology, not a machine learning model that requires a distinct "training set" in the conventional AI sense. While the device's algorithms are developed and refined, the concept of a "training set" as understood in AI studies is not directly applicable or described here.

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

• Not applicable / Not provided. As mentioned above, the concept of a training set with established ground truth, as typically discussed for AI/ML devices, does not apply to this electrochemical blood glucose meter in the context of this 510(k) summary.

In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance data against specific acceptance criteria. The specific numerical performance, sample sizes, and detailed methodology of the performance study are not included in this document.

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