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The Medical Electronic Thermometer (FC0). FC02) is intended to measure the human body temperature under the arm. The devices are reusable for clinical or home use for people of all ages.

The Medical Electronic Thermometer (FC01, FC02) is a hand-held device which can measure human body temperature at the site of the armpit. The devices are reusable for clinical or home use for people of all ages. The results can be displayed on the LCD. The FC01 and FC02 have only one operating mode which is direct mode. The Medical Electronic Thermometer measures human body temperature by placing the probe tip under the armpit with a measuring time of about 300 seconds. The Medical Electronic Thermometer consists of a temperature sensor (NTC), low power integrated circuit (IC), buzzer, and battery. The resistance of sensor changes with temperature and the integrated circuit (IC) converts the resistance to frequency and calculates the temperature according to the relation of resistance and frequency. The calculated temperature is displayed on the LCD.

The provided text is a 510(k) summary for a medical electronic thermometer. It details the device, its intended use, and a comparison to a predicate device to demonstrate substantial equivalence. However, it does not contain information about a study proving the device meets specific acceptance criteria for AI/ML performance, nor does it mention any AI or machine learning components within the device itself.

The document discusses the device's accuracy and performance in relation to established standards for clinical thermometers, which are relevant to device performance but not to the acceptance criteria of an AI/ML model.

Therefore, I cannot fulfill the request to provide acceptance criteria and a study proving an AI/ML device meets those criteria based on the provided text. The text describes a standard medical electronic thermometer and its regulatory clearance process, not an AI-powered device.

To answer your request, if this were an AI/ML medical device, the information you're asking for would typically be found in detailed clinical validation studies, often submitted as part of a 510(k) or PMA submission for AI-driven technologies.

Based only on the provided text, here’s what I can extract regarding device performance, acknowledging that it's for a traditional thermometer, not an AI/ML device:

1. A table of acceptance criteria and the reported device performance

The document refers to adherence to international standards for thermometer performance. The acceptance criteria for the thermometer's performance are defined by these standards, specifically ISO 80601-2-56 and ASTM E1112-00(2018).

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify sample sizes for performance testing. It states that "Performance data were provided in support of the substantial equivalence determination" and lists the standards adhered to. For a traditional thermometer, performance testing generally involves laboratory bench testing rather than large-scale clinical trials with "test sets" in the way an AI/ML model would use them. No information on data provenance (country, retrospective/prospective) is provided, as this is not detailed for a standard thermometer's testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. This device is a standard medical electronic thermometer, not an AI/ML device requiring expert ground truth for image interpretation or diagnosis. Its performance is validated against physical reference standards and established protocols for temperature measurement.

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

Not applicable. See point 3.

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 device is a standard medical electronic thermometer and does not involve AI assistance for human readers/clinicians, nor does it process medical images.

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

Not applicable. The device itself is standalone in its function as a thermometer, but there is no "algorithm" in the sense of an AI/ML model being assessed for standalone performance. Its performance is evaluated against physical measurement standards.

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

The ground truth for thermometer performance is based on traceable temperature standards and established metrology principles, as outlined in the referenced ISO and ASTM standards. It's not based on expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

8. The sample size for the training set

Not applicable. This device does not use a training set as it is not an AI/ML model.

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

Not applicable. See point 8.

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