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FORA Diamond Nexus Mini Thermometer is intended for the intermittent measurement and monitoring of human body temperature from forehead measurement at home.

FORA Diamond Nexus Mini Infrared Forehead Thermometer is characterized by measuring human body temperature from the surface of human skin. It utilizes infrared technology to measure infrared energy emitted from the skin surface when making a temperature measurement.

Here's an analysis of the provided text regarding the acceptance criteria and study for the FORA Diamond Nexus Mini Infrared Forehead Thermometer:

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on non-clinical performance characteristics validated against existing standards (ASTM E1965-98 and EN12470-5). Clinical accuracy is also reported.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Clinical Accuracy Test: 120 subjects (labeled as "Sample size" for the clinical bias and repeatability tables).
• Data Provenance: Not explicitly stated in the provided summary (e.g., country of origin). It is also not specified whether the data was retrospective or prospective.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

This information is not provided in the document. The method for establishing ground truth is not detailed beyond the use of standards. For clinical accuracy, it can be inferred that a reference thermometer was used as a comparative ground truth, but the details of its operation or the involvement of experts in establishing that ground truth are absent.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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, an MRMC comparative effectiveness study was not done. This device is a standalone thermometer, not an AI-assisted diagnostic tool that would involve human readers interpreting images or data alongside AI.

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

• Yes, a standalone performance assessment was done. The entire submission describes the performance characteristics of the thermometer itself, independently measuring and displaying temperature. There is no human-in-the-loop component for reading or interpreting the thermometer's direct output.

7. The Type of Ground Truth Used

• The ground truth for the performance tests (clinical and laboratory accuracy) is implicitly based on established metrological standards and reference devices compliant with those standards (ASTM E1965-98, EN-12470-5). For clinical accuracy, this would typically involve comparison against a highly accurate reference thermometer. For laboratory accuracy, it would involve comparison against calibrated temperature sources. The document does not specify a separate "expert consensus," "pathology," or "outcomes data" as ground truth beyond adherence to these technical standards.

8. The Sample Size for the Training Set

This information is not applicable and therefore not provided. This device is a traditional infrared thermometer, not an AI/machine learning algorithm that requires a training set in that context. The "training" here would be the device's calibration and design against engineering principles and standards, not a dataset in the AI sense.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable as there is no "training set" in the context of an AI algorithm. The device's accuracy and performance are established through adherence to and testing against the specified international standards (ASTM E1965-98 and EN-12470-5).

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