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The Comarch e-Care Platform is intended to connect with physiological measurement devices (weight scales, blood pressure meters, pulse oximeters, peak flow meters, thermometers, glucometers) intended to use at home and send the measurement results to central server. Comarch e-Care Platform serves as Software as a Medical Device and can be used only with FDA cleared measurement devices.

Comarch e-Care Platform displays the collected measurements on the Web application and securely stores them in a database server, where the caregiver can view them, leave comments and contact patient if necessary. Caregivers are able to set thresholds individually for each patient. Measurement results sent to e-Care Platform from connected devices are analyzed and if result is beyond the threshold, caregiver gets the notification.

The Comarch e-Care Platform is not interpretive, nor is it intended for diagnosis or as a substitute for medical care, and it is not intended to provide real time data. It is made available to patients when time-critical care is not required.

The Comarch e-Care Platform is contraindicated for patients requiring direct - medical supervision or emergency intervention. It is intended for patients who are willing and capable of managing its use. Clinical judgment and experience by a caregiver are required to check and interpret the information delivered.

Comarch e-Care Platform is a software intended for use in remote patient monitoring outside of traditional healthcare settings (e.g. at home). Components of Comarch e-Care Platform are: Comarch SMA application, Comarch e-Care application, application server, database server.

Comarch SMA is a software application intended to use by patients. It is designed to collect, display and transmit vital sign measurements captured from commercially available home monitoring devices.

The following vital signs are collected: temperature, glucose, noninvasive blood pressure, pulse oximetry, weight and spirometry.

The Comarch e-Care Platform is a software intended for use in remote patient monitoring outside of traditional healthcare settings (e.g. at home). It connects with physiological measurement devices (weight scales, blood pressure meters, pulse oximeters, peak flow meters, thermometers, spirometers, glucometers) and sends the measurement results to a central server. The platform displays collected measurements on a web application, securely stores them, and allows caregivers to view and analyze them, leave comments, and contact patients. Caregivers can set individual thresholds for each patient, and the platform notifies the caregiver if a measurement result is beyond the set threshold. The device is not interpretive, not intended for diagnosis or as a substitute for medical care, and does not provide real-time data. It is for patients who are able and willing to manage its use, and clinical judgment by a caregiver is required to interpret the information.

Here's an analysis of the acceptance criteria and supporting study information:

1. Table of Acceptance Criteria and Reported Device Performance:

The provided document does not explicitly present a table of quantitative acceptance criteria for device performance. Instead, the substantial equivalence determination for the Comarch e-Care Platform is based on similarities to predicate devices in terms of:

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 states that "no clinical tests were conducted." Therefore, there is no specific test set or data provenance mentioned for clinical performance evaluation. The evaluation was based on non-clinical verification and validation.

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)

Since no clinical tests were conducted and no specific test set-based ground truth was established, this information is not applicable and not provided in the document.

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

Since no clinical tests were conducted and no test set ground truth was established by experts, this information is not applicable and not provided.

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 explicitly states "no clinical tests were conducted." Therefore, no MRMC comparative effectiveness study was done, and no effect size regarding human reader improvement with/without AI assistance is provided.

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

The substantial equivalence is based on the device's functional similarities to predicate devices in remote patient monitoring, data transmission, storage, and caregiver notification, rather than a standalone performance evaluation of a diagnostic algorithm. The device itself is described as "not interpretive" and "not intended for diagnosis." The non-clinical verification and validation focused on the software's functionality and adherence to design specifications. Therefore, a standalone performance study in the context of diagnostic accuracy was not performed for this device.

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

As no clinical tests were performed, there was no "ground truth" derived from patient data, expert consensus, pathology, or outcomes data for the purpose of validating diagnostic or interpretive accuracy. The "ground truth" for the non-clinical verification and validation would have been the design specifications and requirements of the software.

8. The sample size for the training set

The document states "no clinical tests were conducted." This implies that the device did not undergo a process involving a "training set" for machine learning model development in the context of clinical performance. The platform's functionality is about data handling and alerts based on pre-set thresholds, not on learning from a dataset to perform interpretations. Therefore, this information is not applicable and not provided.

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

As no training set was used for clinical performance evaluation, this information is not applicable and not provided.

In summary, the Comarch e-Care Platform's acceptance was based on a demonstration of substantial equivalence to existing predicate devices through comprehensive non-clinical verification and validation testing, ensuring the software's functionality, adherence to design specifications, and addressing identified risks. No clinical studies or performance evaluations requiring test sets, ground truth establishment, or expert adjudication were conducted, as the device is not interpretive and does not provide diagnostic insights.

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The Optum TeleHealth Application is a software application designed to retrospectively monitor vital signs. The following vital signs are collected: noninvasive blood pressure, pulse rate, weight, temperature, and blood glucose. The Optum TeleHealth Application collects, displays, and transmits vital sign measurements captured from commercially available FDA cleared medical devices designed for home use, or via manual input by the patient. Collected measurement data from the Optum TeleHealth Application can be transmitted via a secure communication mechanism to a central health data repository. Data can be viewed and analyzed via the Optum TeleHealth Web Application.

The Optum TeleHealth Application is not intended for emergency use or real-time monitoring.

The client application is available in three configurations:

• stand-alone application for both Android and iOS operating systems
• pre-loaded on an Android tablet

The Optum TeleHealth Application is client/server software application which collects and transmits patient vital signs, and physiological data for review, and analysis by clinicians. The software consists of a web based application for clinician use, the client application for member use, and web services. Standard data communication protocols are used. The server hosts the web based application for user management, and patient information and care management. The client application is designed to work with Android devices (OS 4.0 and higher) and Apple devices (iOS 9 and higher), and allows for data input from external biometric measuring devices, review of clinician advice, response to clinician questions, and viewing of graphed data.

The client application is available in two configurations:

• stand-alone application for both Android and iOS operating systems .
• . pre-loaded on an Android tablet

The device is used in combination with various Class I 510(k) exempt devices and FDA cleared biometric measuring devices, including, but not limited to:

• A&D Medical, UA-767PBT Digital Blood Pressure Monitor (K043217) .
• . A&D Engineering Inc., UC-321PBT Weight Scale (510(k) exempt)
• TaiDoc Technology Corporation, Fora W310 Weight Scale (510(k) exempt) .
• . TaiDoc Technology Corporation, Fora IR20b Ear Thermometer (K090395)
• TaiDoc Technology Corporation, Fora P20 Blood Pressure Monitor (K092106) ●
• Nonin Medical Inc Onyx II Model 9560 Finger Pulse Oximeter (K081285) ●

The provided document is a 510(k) premarket notification letter and summary for the Optum TeleHealth Application. It describes a software application designed to collect, display, and transmit vital sign measurements for retrospective monitoring. As such, it is a data handling and transmission device, not a diagnostic or prognostic medical imaging AI device.

Therefore, the document does not contain the information requested for acceptance criteria and a study proving device performance as typically expected for a medical imaging AI device. Specifically, it does not include:

• A table of acceptance criteria with reported device performance (e.g., sensitivity, specificity, AUC).
• Details on sample size, data provenance, ground truth establishment, or expert involvement for a test set designed to evaluate diagnostic or prognostic performance.
• Information on MRMC studies or standalone algorithm performance.

Instead, the document focuses on:

• Indications for Use: Retrospective monitoring of vital signs (noninvasive blood pressure, pulse rate, weight, temperature, blood glucose). It explicitly states it's not intended for emergency use or real-time monitoring.
• Technological Characteristics: How it collects data (manual input, Bluetooth from external devices) and transmits it to a central repository.
• Predicate Devices: Claiming substantial equivalence to a previously cleared Optum TeleHealth Application (K130971).
• Pre-Clinical Testing: A generic statement that "Bench testing, including software validation, was performed to ensure that the product works as intended." and "Results of bench testing show that the product is safe, and effective for use." This implies functional verification and validation of the software, rather than clinical performance evaluation against a diagnostic ground truth.

In summary, this device's function is data aggregation and transmission, not medical image analysis or diagnosis. The typical performance metrics and study designs (like MRMC, standalone performance, or detailed ground truth establishment for diagnostic accuracy) are not applicable or described for this type of device in the provided document.

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Measure blood pressure (systolic and diastolic) and pulse rate.

UB-1100BLE UltraConnect digital blood pressure monitor has the same design as the predicate devices with an inflatable cuff which is wrapped around the patient's wrist. After the user starts the blood pressure measurement, the cuff is inflated automatically by an internal pump. The systolic and diastolic blood pressures are also determined by oscillometric method. The deflation rate is controlled by an internal exhaust valve. There is a quick exhaust mechanism so that the cuff pressure can be completely released immediately. There is a maximum pressure safety setting at 299 mmHg. UB-1100BLE UltraConnect digital blood pressure monitor will not inflate the cuff higher than 299 mmHg. UB-1100BLE will turn on an irregular heartbeat indicator if an irregular heartbeat was detected during the measurement process. At the end of the measurement, the systolic and diastolic pressures with pulse rate are shown on the OLED and transmitted via Bluetooth wireless module to the connected app. The cuff is also deflated automatically to 0 mmHg at the same time. If the monitor receives no further action from the user for 1 minute, it will automatically turn off by itself.

This document is a 510(k) premarket notification for a blood pressure monitor, not an AI/ML medical device. Therefore, much of the requested information regarding AI acceptance criteria, ground truth, expert adjudication, and MRMC studies is not applicable.

However, I can extract information related to the device's performance and the general testing methodology for this type of medical device as presented in the document.

Acceptance Criteria and Device Performance (based on the provided specifications for a blood pressure monitor):

The acceptance criteria for a non-invasive blood pressure measurement system like the UB-1100BLE are typically defined by recognized standards such as AAMI/ANSI/IEC 80601-2-30.

Study Proving Device Meets Acceptance Criteria:

The document states: "There is no modification requiring conducting clinical tests." This indicates that the device's performance was not proven through a new clinical study. Instead, substantial equivalence was demonstrated based on its similarities to previously cleared predicate devices and adherence to relevant standards.

Detailed Breakdown of Information as applicable to this medical device submission:

1. A table of acceptance criteria and the reported device performance:
   (See table above)

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

   • Sample Size: Not applicable as no new clinical test set was used to prove the device's performance. The submission relies on the established performance of its predicate devices and non-clinical testing for equivalence.
   • Data Provenance: Not applicable for a new clinical test set. The predicate devices' performance data would have originated from their respective clinical trials and validation studies, the details of which are not in this document. The current submission focuses on non-clinical tests (e.g., electrical safety, EMC, reliability) to demonstrate that the modifications did not alter the fundamental performance.

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, as this is a blood pressure monitor and not an AI/ML diagnostic imaging device that requires expert human interpretation for ground truth.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
   Not applicable, as there was no test set requiring adjudication in the context of a new clinical study.

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 standalone blood pressure monitor and does not involve AI assistance for human readers/clinicians, nor does it conduct diagnostic tasks in the way an imaging AI would.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   The device itself operates as a standalone blood pressure measurement system (algorithm only for generating BP readings) in the sense that it provides measurements directly. However, the context of this question usually refers to AI algorithms performing a diagnostic task. In that sense, it's not directly comparable. The performance (accuracy of BP and pulse readings) is what defines its standalone performance, and that's assessed against physical standards and other measurement devices rather than human interpretation.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   For blood pressure monitors, the "ground truth" is typically established by comparative measurements against a reference standard or invasively measured blood pressure, or through clinical validation according to protocols like those outlined in the AAMI/ANSI/IEC 80601-2-30 standard. It's not based on expert consensus or pathology in the typical sense of AI/ML diagnostic tools.

8. The sample size for the training set:
   Not applicable. This device does not use machine learning in a way that requires a "training set" in the context of AI/ML model development. It uses an oscillometric method, which is a classical signal processing technique.

9. How the ground truth for the training set was established:
   Not applicable, as there is no training set for an AI/ML model.

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TM-2657, TM-2657P, TM-2657PBT, and TM-2657PRS are designed to measure blood pressure (systolic and diastolic) and pulse rate in adult patients with arm circumference range between 7.1 inches (18.0 cm) and 13.8 inches (35.0 cm)

TM-2657 Family of digital blood pressure monitors have the same design as the predicated devices with an inflatable cuff which is wrapped around the patient's upper arm. After the user pushes the "START" button, the cuff is inflated automatically by an internal pump. The systolic and diastolic blood pressures are also determined by oscillometric method. The deflation rate is controlled by an internal exhaust valve. There is a quick exhaust mechanism so that the cuff pressure can be completely released urgently. There is a maximum pressure safety setting at 299 mmHg. TM-2657 Family of digital blood pressure monitors will not inflate the cuff higher than 299 mmHg. TM-2657 Family of digital blood pressure monitors will turn on an irregular heartbeat indicator if an irregular heartbeat was detected during the measurement process. At the end of the measurement, the systolic and diastolic pressures with pulse rate are shown on the LCD and printed by the internal printer or transmitted via Bluetooth wireless module if it is installed. The cuff is also deflated automatically to 0 mmHg at the same time.

Here's a breakdown of the acceptance criteria and study information for the A&D Medical TM-2657 Family of Digital Blood Pressure Monitors, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: 85 subjects.
• Data Provenance: Not explicitly stated regarding country of origin or whether it was retrospective/prospective. However, the study was a clinical test based on BS EN 1060-4:2004 / ISO 141155-1 & -2:2003, which are international standards for sphygmomanometers, implying a clinical study setting.

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

• Number of Experts (Observers): 2
• Qualifications of Experts: The document states "Observer: 2" but does not explicitly mention their qualifications (e.g., medical professionals, specific experience). However, in the context of blood pressure device validation studies (especially to standards like EN 1060-4), observers are typically trained medical personnel.

4. Adjudication Method for the Test Set

• The document implies a comparison between the device's readings and those of the two human observers. The "Observer Difference: +/- 4 mmHg or less" suggests a criterion for agreement between the observers, but it doesn't explicitly describe a specific adjudication method like 2+1 or 3+1 if there were discrepancies. The "Measurement Result: Average" and "S.D." likely refer to the agreement between the device and the calibrated observer readings.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, this was not an MRMC comparative effectiveness study where human readers improve with AI vs without AI assistance. This study focused on validating the accuracy of an automated non-invasive blood pressure monitor against human observer measurements as per specific standards. The device is a standalone blood pressure monitor, not an AI-assisted diagnostic tool.

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

• Yes, this study primarily represents a standalone performance evaluation of the A&D Medical TM-2657 device. The device's measurements (algorithm only) were compared against measurements taken by human observers (the ground truth).

7. The Type of Ground Truth Used

• The ground truth used for the test set was expert reference measurements. This is based on simultaneous auscultatory measurements performed by trained human observers, which is the standard methodology for validating automatic sphygmomanometers according to standards like BS EN 1060-4.

8. The Sample Size for the Training Set

• The document does not provide information on the sample size used for the training set. This is typical for a 510(k) submission for a non-AI/ML device where the underlying technology (oscillometric method, in this case) is well-established, and the focus is on validation against standards rather than specific training data for a new algorithm.

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

• As no information on a training set is provided, there is no information on how its ground truth was established. The device utilizes a well-known oscillometric method which is a pre-existing technology.

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The Optum TeleHealth Application is a software application designed to retrospectively monitor vital signs. The following vital signs are collected: noninvasive blood pressure, pulse oximetry, pulse rate, weight, temperature, and blood glucose. The Optum TeleHealth Application collects, displays, and transmits vital sign measurements captured from commercially available FDA cleared medical devices designed for home use, or via manual input by the patient. Collected measurement data from the Optum TeleHealth Application can be transmitted via a secure communication mechanism to a central health data repository. Data can be viewed and analyzed via the Optum TeleHealth Web Application.

The Optum TeleHealth Application is not intended for emergency use or real-time monitoring.

The client application is available in two configurations:

• stand-alone application .
• pre-loaded on an Android tablet .

The Optum TeleHealth Application is client/server software application which collects and transmits patient vital signs, and physiological data for review, and analysis by clinicians.

The software consists of a web based application for clinician use, the client application for member use, and web services. Standard data communication protocols are used. The server hosts the web based application for user management, and patient information and care management. The client application is designed to work with Android tablets (Android OS 4.0 and higher), and allows for data input from external biometric measuring devices, review of clinician advice, response to clinician questions, and viewing of graphed data.

The client application is available in two configurations:

• stand-alone application .

• pre-loaded on an Android tablet .
  The device is used in combination with various Class I 510(k) exempt devices and FDA cleared biometric measuring devices, as listed below:

• A&D Medical, UA-767PBT Digital Blood Pressure Monitor (K043217)

• A&D Engineering Inc., UC-321PBT Weight Scale (510(k) exempt)

• TaiDoc Technology Corporation, Fora W310 Weight Scale (510(k) exempt) .

• TaiDoc Technology Corporation, Fora IR20b Ear Thermometer (K090395) .

• TaiDoc Technology Corporation, Fora P20 Blood Pressure Monitor (K092106) .

• Nonin Medical Inc Onyx II Model 9560 Finger Pulse Oximeter (K081285) .

The Optum TeleHealth Application is a software application designed to collect, display, and transmit patient vital signs and physiological data for review and analysis by clinicians. The device is not intended for emergency use or real-time monitoring.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a distinct "test set" in the context of a clinical study with patients. The testing performed was "Bench testing, including software validation." This typically involves internal testing by developers rather than a separate patient-based test set for performance evaluation. Therefore, information on data provenance (country of origin, retrospective/prospective) is not applicable.

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

This information is not applicable as the testing described is limited to "bench testing" and "software validation," not a clinical study requiring expert-established ground truth.

4. Adjudication method for the test set

This information is not applicable as the testing described is limited to "bench testing" and "software validation," not a clinical study 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

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. The device is a data collection and transmission application, not an AI-powered diagnostic tool requiring human reader interpretation improvements.

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

The device itself is a standalone software application in the sense that it operates independently to collect and transmit data. However, its intended use inherently involves a "human-in-the-loop" (clinicians reviewing and analyzing the data). No study focused on "algorithm only without human-in-the-loop performance" was explicitly mentioned, other than software validation.

7. The type of ground truth used

For the "bench testing" and "software validation," the ground truth would likely be established through predefined software requirements, expected output values for simulated inputs, and adherence to communication protocols. It would not typically involve expert consensus, pathology, or outcomes data in the way a diagnostic device would.

8. The sample size for the training set

The document does not mention a "training set." This type of testing is characteristic of traditional software validation, not machine learning model training as understood in current AI contexts.

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

Not applicable, as no training set for a machine learning model was identified. The device's validation relied on traditional software testing methodologies.

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The TensorTip - Non-invasive Hemodynamic blood pressure monitor trending device is a small, lightweight, handheld, device intended for measuring and display of Blood Pressure trending (systolic and diastolic) and spot-check of Peripheral pulse rate (PPR) and Peripheral pulse wave (PPW). Measurement is performing on capillary finger tip tissue (other than the thumb). The ring finger is the recommended site. The results of each measurement are stored in the system memory. The device is intended for use in the home environment. It is intended to be used by any person aged above 18 years old.

The TensorTip - Non-invasive Hemodynamic Blood Pressure Monitor measurement chamber is designed to measure spot-check of heartbeat and blood pressure trending levels by simply inserting the finger into the device "chamber". It contains a dedicated finger compartment having soft gel on the upper compartment lead door suiting the finger to be placed inside. The device incorporates LEDs (Light Emitting Diode); a sensor array enables to sense the spectrum from near UV to near IR and a rechargeable battery for power supply. The device has large display for displaying temporal Pulse Per Minute (PPM) and Systolic and Diastolic Blood Pressure trending. In addition it shows the capillary blood waveform and the blood pressure variation during the measurement period. It is utilizing software that collects and presents the measured data.

Here's a breakdown of the acceptance criteria and study information for the Cnoga Medical TensorTip, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary primarily focuses on demonstrating substantial equivalence to predicate devices and adherence to relevant standards. Specific numerical acceptance criteria for blood pressure accuracy (e.g., mean difference and standard deviation compared to a reference method) are not explicitly stated in the provided text. However, the summary indicates that clinical validation met the requirements of ISO 81060-2, which is the standard for non-invasive sphygmomanometers. This standard typically defines accuracy requirements.

Since the exact numerical acceptance criteria are not specified, the table will reflect the general statement of conformity to the standard.

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

• Sample Size for Test Set: Not explicitly stated in the provided text. The document only mentions "human testing" for clinical validation.
• Data Provenance: Not explicitly stated. The document indicates "human" testing was performed, but does not specify the country of origin of the data or whether it was retrospective or prospective.

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

This information is not provided in the given 510(k) summary. For blood pressure monitors, ground truth is typically established by trained medical professionals using a reference device (e.g., a mercury sphygmomanometer or an oscillometric device validated against an invasive arterial line).

4. Adjudication Method for the Test Set

This information is not provided in the given 510(k) summary.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not applicable or not provided. The device described is a non-invasive hemodynamic blood pressure monitor, not an AI-assisted diagnostic imaging system that would typically involve human "readers" or an MRMC study in this context. The 510(k) describes a standalone device.

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

Yes, a standalone performance study was done. The 510(k) describes the TensorTip as a device that directly measures and displays blood pressure and pulse rate. The "Performance Data" section states that "Cnoga Medical's TensorTip spot-check pulse rate and non-invasive blood pressure trending device has been successfully tested with bench, human and safety testing to support the determination of substantial equivalence with predicate devices." This implies testing the device's inherent accuracy in measuring these physiological parameters.

7. The Type of Ground Truth Used

The ground truth used for clinical validation of blood pressure devices typically involves measurements from a validated reference device (e.g., a mercury sphygmomanometer or an oscillometric device that has itself been validated against more invasive methods like intra-arterial pressure). While not explicitly detailed, the statement "Clinical validation has met the requirement of ISO 81060-2 standard" strongly implies that such a reference standard was used to establish ground truth for the test set.

8. The Sample Size for the Training Set

This information is not provided in the given 510(k) summary. The document describes a medical device, not a machine learning model that typically involves a distinct "training set" in the conventional sense of AI development. While the device certainly uses algorithms, the summary doesn't parse out data into training/test sets in that manner.

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

This information is not provided as a separate "training set" and its ground truth establishment are not directly discussed in the context of the device's development as presented in this 510(k) summary. The focus is on the device's overall performance validation against standards.

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