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The AG Thermographic Camera(Model no.: ATIR M301) is intended to use as an adjunct to other clinical diagnostic procedures by quantifying differences in skin surface temperature changes. It can visualize and digitalize body surface temperature distribution and temperature changes. The device is intended for use by qualified healthcare personnel trained in its use.

The AG Thermographic Camera (Model no.: ATIR-M301) consists of an infrared camera, accessories, and PC visualization/analysis software. It is a non-contact, non-invasive, and non-radiating infrared system capable of imaging and storing thermal patterns generated by the human body. It employs passive infrared emission sensing technology to capture the thermal data and uses proprietary software to display the temperature distribution pattern as an image.

This document describes the AG Thermographic Camera, Model no.: ATIR-M301, a telethermographic system.

Here's an analysis of the provided text regarding acceptance criteria and the study that proves the device meets them:

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

The document lists performance tests conducted, implying these serve as acceptance criteria. The specific numerical acceptance criteria values are largely absent, except for temperature accuracy.

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 explicitly state the sample size used for any of the performance tests. It also does not provide information on the data provenance (e.g., country of origin, retrospective or prospective nature of the data). Given the device's nature (a thermal camera), the performance tests likely involved physical measurements rather than patient data.

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)

The document does not mention the use of experts to establish ground truth for the test set. The performance tests described (e.g., temperature accuracy, focus test) are technical validations of the device's functionality, which typically rely on calibrated reference standards and engineering measurements rather than expert clinical interpretation.

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

The document does not describe any adjudication method. This is consistent with the nature of the described performance tests, which are objective engineering measurements rather than subjective interpretations requiring adjudication.

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

The document does not mention or describe a multi-reader multi-case (MRMC) comparative effectiveness study. This device is a standalone imaging system, not an AI-assisted diagnostic tool for human readers in the context of comparative effectiveness for clinical interpretations.

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

Yes, the performance tests described are for the standalone device (algorithm for displaying thermal patterns and temperature measurements). The document states, "Performance tests including · Temperature accuracy • Environment temperature factor test · Focus test · Distanced object temperature test · Thermal image handling · Small area temperature statistics and two-area comparison · Patient history record handling were conducted to ensure the device can work as the intended performance." These tests evaluate the device's inherent capability to perform its functions without human interpretation as part of the performance metric.

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

For the performance tests, the ground truth would be established by calibrated reference standards and physical measurements. For example, for "Temperature accuracy," the ground truth would be from a precisely known and stable temperature source measured by a highly accurate reference thermometer. For "Focus test," it would be based on objective image quality metrics. There is no mention of expert consensus, pathology, or outcomes data being used as ground truth for these device performance validations.

8. The sample size for the training set

The document does not mention any training set or machine learning components. This device is described as employing "passive infrared emission sensing technology to capture the thermal data and uses proprietary software to display the temperature distribution pattern as an image." It's a sensor system with display and analysis software, not a machine learning model that requires a training set.

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

Since there is no mention of a training set, the document does not describe how ground truth for a training set was established.

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