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The FilteredFlo Warming Blanket is intended to be used with the IOB-507 patient warming system. The IOB-507 Temperature Management system is indicated for hypothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated. These blankets are intended for adult and pediatric use.

The FilteredFlo warming blankets are used with the IOB Temperature Management System (previously cleared K231596) that draws ambient- temperature air through a 0.2 micron particulate air filter. The filtered air is warmed to a selected temperature. The warmed air enters the FilteredFlo Warming Blanket through the hose and is distributed through delivery channels. Perforations on the patient side of the air delivery channels in the warming blanket gently disperse the warmed air over and around the patient.

The FilteredFlo warming blankets in the submission are the following:

FF-243 ADULT/PACU BLANKET
FF-244 PEDIATRIC BLANKET
FF-246 INFANT UNDERBODY BLANKET
FF-247 LARGE PEDIATRIC UNDERBODY BLANKET
FF-248 ADULT UNDERBODY BLANKET
FF-443 UPPER BODY BLANKET
FF-442 LOWER BODY BLANKET
FF-344 TORSO BLANKET
FF-145 WARMING TUBE BLANKET

These blankets are single-use and disposable. Each blanket consists of two layers of nonwoven polypropylene fabric coated with a layer of polyethylene. The layers are bonded together to form a distribution network of air delivery channels. The warm air is distributed around the blanket through the delivery channels and exits the blanket through a specially designed series of perforations in the patient side of the blanket.

The provided document is a 510(k) summary for a medical device called "FilteredFlo Warming Blankets." It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain information related to software, artificial intelligence (AI), diagnostic performance, or extensive clinical studies that would typically have the requested details about acceptance criteria for AI models, human reader studies, ground truth establishment, or training/test set sizes.

The "studies" mentioned are primarily non-clinical tests to demonstrate that the new warming blankets perform equivalently to existing ones in terms of physical characteristics and safety, not diagnostic accuracy or AI performance.

Therefore, I cannot provide the requested information for acceptance criteria and studies related to AI or diagnostic performance, as these are not relevant to the "FilteredFlo Warming Blankets" device as described in this 510(k) submission.

Here's a breakdown of what can be extracted from the document, tailored as much as possible to your request, but highlighting the absence of AI/diagnostic-specific details:

Device: FilteredFlo Warming Blankets (models FF-243, FF-244, FF-246, FF-247, FF-248, FF-443, FF-442, FF-344, FF-145)

Intended Use: "The FilteredFlo Warming Blanket is intended to be used with the IOB-507 patient warming system. The IOB-507 Temperature Management system is indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated. These blankets are intended for adult and pediatric use."

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

   Since this is a thermal regulating system and not an AI or diagnostic device, the "acceptance criteria" are related to physical and functional equivalence to a predicate device, specifically in terms of temperature uniformity, package integrity, and lack of leaks.

   Acceptance Criteria	Reported Device Performance
   Temperature Uniformity	All test results show temperature uniformity "equivalence" between the FilteredFlo Warming Blankets and the predicate at different IOB Warmer settings.
   Simulated Transport Testing (ASTM D4169)	No package damage was observed. All products held integrity after the transport testing.
   Bubble Testing (ASTM F2096) (Leakage)	No leakage was found.
   Biocompatibility	Tests for biocompatibility were reported in the previously cleared K231596 (predicate device's clearance). The proposed device is implicitly accepted as biocompatible based on previous clearance.
   Material Design and Indication for Use Equivalence	The proposed device's material design and Indications for Use are deemed "Substantially Equivalent" to the predicate device.

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

   • Sample Size: Not explicitly stated for each test, but implied to be a representative sample of the different blanket models. These are physical product tests, not data-driven studies with "test sets" in the AI sense.
   • Data Provenance: Not specified, but these are laboratory/bench tests performed by the manufacturer or their contractors.

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. "Ground truth" in this context refers to established engineering standards and physical measurements, rather than expert diagnostic consensus.

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

   Not applicable. These are engineering and physical product tests, not qualitative assessments requiring adjudication. The results are based on objective measurements against defined criteria.

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 warming blanket, not an AI or diagnostic tool. No MRMC study was performed or is relevant.

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

   Not applicable. This is a physical medical device, not an algorithm.

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

   The "ground truth" for demonstrating performance is derived from established engineering standards (e.g., ASTM standards for transport and bubble testing) and physical measurements (e.g., temperature measurements for uniformity). Comparison to the predicate device's cleared performance serves as the benchmark for "equivalence."

8. The sample size for the training set

   Not applicable. This device does not involve a "training set" for an algorithm.

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

   Not applicable.

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The IOB Temperature Management System Model IOB-507 is indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated.

The IOB Temperature Management System Model IOB-507 consists of the IOB Warming Unit and the IOB Warming Blankets. The IOB Warming Unit, model IOB-507, draws ambient- temperature air through a 0.2 micron air filter. The filtered air is warmed to a selected temperature. The warmed air enters the IOB Warming Blanket through the hose and is distributed through delivery channels. Perforations on the patient side of the air delivery channels in the warming blanket gently disperse the warmed air over and around the patient. The warming unit has three temperature settings of 32℃, 38℃, and 43℃. These temperature settings are servo-controlled by a thermistor placed at the end of the hose where the hose connects to the blanket. The unit can also deliver ambient-temperature air. The temperature indicated on the control panel is the temperature of air being delivered to the average contact surface temperature of the blanket. A control thermistor in the warming unit adjusts the power applied to the heater to maintain the selected temperature. This enables the unit to maintain the selected temperature under variations in ambient temperature. Besides, the warming unit has high and low air flow options. A safety thermistor provides a signal to a separate high-temperature analog circuit. The safety thermistor activates and produces an alarm if the temperature exceeds the set point. The analog safety circuit provides an independent means of shutoff, which discontinues power to the heater and motor. This prevents patient exposure to excessive temperatures. IOB warming blankets are single-use and disposable. Each blanket consists of two layers of non-woven polypropylene fabric coated with a layer of polyethylene. The layers are bonded together to form a distribution network of air delivery channels. The warm air is distributed around the blanket through the delivery channels and exits the blanket through a specially designed series of perforations in the patient side of the blanket.

The document describes the IOB Temperature Management System Model IOB-507, which includes the IOB Warming Unit and IOB Warming Blankets. The system is indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated. The device is a Class II device with product code DWJ (Thermal regulating system).

No clinical studies were performed. The device's substantial equivalence determination is based on non-clinical tests. Therefore, there is no information about acceptance criteria or a study that proves the device meets specific acceptance criteria in the context of human performance or clinical outcomes.

However, based on the non-clinical tests mentioned, we can infer some performance characteristics and the tests conducted to demonstrate them.

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

Since no specific acceptance criteria for clinical performance are provided, this table focuses on the performance characteristics assessed through non-clinical testing.

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 provide details on the sample size for non-clinical tests (e.g., how many units of the warming unit or blankets were tested for each criterion). The data provenance is not mentioned, but as these are non-clinical (laboratory) tests, the concept of "country of origin of the data," "retrospective," or "prospective" as typically applied to clinical studies is not directly relevant. These tests would have been performed in a controlled laboratory environment by the manufacturer or a third-party testing facility.

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)

This information is not applicable. The non-clinical tests described (electrical safety, temperature accuracy, material stability, etc.) do not involve human interpretation or the establishment of ground truth by clinical experts. These are objective engineering and material science tests.

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

This information is not applicable. Adjudication methods are relevant for clinical studies or image interpretation tasks performed by multiple human readers, which is not the case here.

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 MRMC study was done, as this device does not involve AI or human readers for diagnostic interpretation. It is a temperature management system.

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

This information is not applicable. The device is a physical temperature management system, not an algorithm.

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

This information is not applicable. The non-clinical tests described use objective physical measurements and established engineering and material science standards (e.g., IEC, ASTM, ISO) as their "ground truth" or reference for evaluating performance.

8. The sample size for the training set

This information is not applicable, as this is a non-AI/ML device.

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

This information is not applicable, as this is a non-AI/ML device.

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The IOB Warming Blankets are indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated.

The IOB warming blankets are used with the IOB Temperature Management System (previously cleared K162679) that draws ambient- temperature air through a 0.2 micron particulate air filter. The filtered air is warmed to a selected temperature. The warmed air enters the IOB Warming Blanket through the hose and is distributed through delivery channels. Perforations on the patient side of the air delivery channels in the warming blanket gently disperse the warmed air over and around the patient.

These blankets are single-use and disposable. Each blanket consists of two layers of non-woven polypropylene fabric coated with a layer of polyethylene. The layers are bonded together to form a distribution network of air delivery channels. The warm air is distributed around the blanket through the delivery channels and exits the blanket through a specially designed series of perforations in the patient side of the blanket.

The provided text describes information about the IOB Warming Blankets, but does not contain details about acceptance criteria or a study proving the device meets those criteria in the context of an AI/ML device.

The document is a 510(k) summary for a medical device (IOB Warming Blankets) for thermal regulation, arguing for substantial equivalence to a predicate device. It focuses on the physical and functional characteristics of the warming blankets themselves (e.g., material, dimensions, shelf life, sterility) and standard non-clinical tests (temperature uniformity, stability, transport testing, bubble testing, biocompatibility).

There is no mention of AI or machine learning, nor any performance metrics that would typically apply to such devices (e.g., sensitivity, specificity, AUC). Therefore, I cannot extract the information requested in your prompt regarding acceptance criteria and studies for an AI/ML device from the provided text.

The closest relevant information, though not for an AI/ML device, is related to the performance of the warming blankets:

Non-Clinical Tests:

• Temperature uniformity tests: Measured five testing points on the blanket surface at different IOB Warmer settings.
• Real-time stability tests: Showed a three-year shelf-life.
• Simulated transport testing: Performed according to ASTM D4169.
• Bubble testing: Carried out according to ASTM F2096.
• Biocompatibility tests: Reported in the previously cleared K162679.

Reported Performance/Results from Non-Clinical Tests:

• Temperature uniformity equivalence: "All test results show temperature uniformity equivalence between the IOB warming blankets and the predicate."
• Shelf-life: "three years shelf-life"
• Transport testing: "No package damage was observed. All product hold integrity after the transport testing."
• Bubble testing: "No leakage was found."

However, this does not align with the acceptance criteria and study proving device performance as typically described for an AI/ML device.

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The ivi N3003 Surgical Face Masks are intended to be worn to protect both the patient and healthcare personnel from transfer of microorganisms, body fluids and particulate material. These face masks are intended for use in infection control practices to reduce the potential exposure to blood and body fluids. This is a single use, disposable device, provided non-sterile.

The ivi N6006 Surgical Mask is single-use, disposable device, provided non-sterile, and intended to be worn by operating room personnel or other healthcare workers to protect both the patient and operating room personnel from the transfer of microorganisms, body fluids, and particulate material.

Not Found

I am sorry, but the provided text from the FDA 510(k) clearance letter for the "ivi N3003 Surgical Face Mask" and "ivi N6006 Surgical Mask" does not contain any information regarding acceptance criteria or a study that proves the device meets acceptance criteria in the context of an AI/ML medical device.

The document is a standard FDA clearance letter for a Class II medical device (surgical masks), focusing on:

• Substantial equivalence determination.
• Regulatory requirements (registration, listing, GMP, labeling, etc.).
• Indications for Use for both mask models.
• Paperwork Reduction Act information.

It does not describe the technical performance of the masks (e.g., filtration efficiency, breathability) or any studies related to proving such performance beyond stating their intended use for protection against microorganisms, body fluids, and particulate material. There is no mention of AI, machine learning, or software-driven device performance.

Therefore, I cannot provide the requested information, which typically applies to AI/ML device submissions, based on the content of this document.

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The IOB Warming Blankets are indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated.

The IOB warming blankets are used with the IOB Temperature Management System (previously cleared K162679) that draws ambient- temperature air through a 0.2 micron particulate air filter. The filtered air is warmed to a selected temperature. The warmed air enters the IOB Warming Blanket through the hose and is distributed through delivery channels. Perforations on the patient side of the air delivery channels in the warming blanket gently disperse the warmed air over and around the patient..

The IOB Warming Blankets in this submission are the following:

Jackson Warming Blanket IOB-024
Infant Full Body/Under Body Blanket IOB-025
Large Half Body Blanket IOB-026
Large Full Body Blanket IOB-027
Infant Under Body Blanket IOB-028
Lithotomy/Orthopedic Under Body Blanket IOB-029
Small Size Warming Suit IOB-301
Medium Size Warming Suit IOB-302
Large Size Warming Suit IOB-303
Extra Large Size Warming Suit IOB-304

These blankets are single-use and disposable. Each blanket consists of two layers of non-woven polypropylene fabric coated with a layer of polyethylene. The layers are bonded together to form a distribution network of air delivery channels. The warm air is distributed around the blanket through the delivery channels and exits the blanket through a specially designed series of perforations in the patient side of the blanket.

The provided text is a 510(k) summary for the IOB Warming Blankets (K190221). It describes the device, its intended use, and its substantial equivalence to a predicate device (K162679 IOB Temperature Management System).

However, the information requested about acceptance criteria and the study that proves the device meets the acceptance criteria, particularly regarding details like sample sizes, expert involvement, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for AI/Machine Learning-based medical devices, is not present in this document.

This document pertains to a Class II medical device (Thermal Regulating System), which falls under a different regulatory pathway than AI-powered diagnostic or predictive tools. The approval here is based on substantial equivalence to a predicate, not necessarily on a de novo clinical performance study against specific acceptance criteria for AI model performance.

The document states:

• "Clinical Studies Not applicable" (Section 10, point 4)
• The safety and performance characteristics mentioned are related to:
  • Temperature uniformity tests: "show equivalence between the IOB warming blankets and the predicate." (This implies a comparison, but not detailed acceptance criteria or methodology for an AI-based system).
  • Accelerated stability tests: "show three years shelf-life of the IOB warming blankets." (This is a physical product test, not AI performance).
  • Biocompatibility tests: "were reported in the previously cleared K162679." (Again, physical product testing).

Therefore, I cannot provide the requested table and detailed information as the provided text does not contain data related to the performance evaluation of an AI/ML-based medical device against acceptance criteria.

The prompt's questions are highly specific to the evaluation of AI/ML algorithms, which is not the subject of this 510(k) submission.

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The IOB Temperature Management system is indicated for hypothermic patients or normothermic patients for whom induced hyperthermia or localized increase in temperature is clinically indicated.

The IOB Temperature Management System consists of the IOB warming unit and the IOB warming blankets. The IOB warming unit draws ambient- temperature air through a 0.2 micron air filter. The filtered air is warmed to a selected temperature. The warmed air enters the IOB Warming Blanket through the hose and is distributed through delivery channels. Perforations on the patient side of the air delivery channels in the warming blanket gently disperse the warmed air over and around the patient. The warming unit has three temperature settings of 32°C, 38°C, and 43°C. These temperature settings are servo-controlled by a thermistor placed at the end of hose where the hose connects to the blanket. The unit can also delivers ambient-temperature air. The temperature indicated on the control panel is the temperature of air being delivered to the blanket at the end of the hose. A control thermistor in the warming unit adjusts the power applied to the heater to maintain the selected temperature. This enables the system to maintain the selected temperature under variations in ambient temperature. Besides, the warming unit has high and low air flow for choose.

The IOB Warming Blankets in this submission are the following:
Torso IOB-001 Lower Body IOB-002 Upper Body IOB-003 Full Body IOB-004 Pediatric Underbody IOB-005 Adult Underbody IOB-006 Pediatric Full Body IOB-007 Full Body Surgical IOB-008 Large Pediatric Underbody IOB-009 Spinal Underbody IOB-010 Lithotomy Underbody IOB-011 Pediatric Lower Body IOB-012 Pediatric Long IOB-014 Cath Lab IOB-015 Surgical Access IOB-016 Chest Access IOB-017 Multi-Access IOB-018 Dual Port Torso IOB-019 Cardiac Access IOB-020 XL Upper Body IOB-021 Outpatient Care IOB-022 Cardiac IOB-023
These blankets are single-use and disposable. Each blanket consists of two lavers of non-woven polypropylene fabric coated with a layer of polyethylene. The lavers are bonded together to form a distribution network of air delivery channels. The warm air is distributed around the blanket through the delivery channels and exits the blanket through a specially designed series of perforations in the patient side of the blanket.

The provided text is a 510(k) summary for the IOB Temperature Management System, which is a medical device for warming patients. It addresses substantial equivalence to a predicate device (Bair Hugger Temperature Management System) rather than outlining acceptance criteria and a study proving device performance in the context of an AI/ML powered device.

Therefore, the specific information requested about acceptance criteria and studies demonstrating performance as would be expected for an AI/ML driven diagnostic or assistive technology (e.g., sample sizes, ground truth establishment, expert adjudication, MRMC studies, standalone performance) is not present in the provided document.

The document focuses on the physical and functional characteristics of a thermal regulating system and its blankets, demonstrating its equivalence to a legally marketed predicate device.

However, I can extract the safety and performance characteristics mentioned in the document, which serve a similar purpose of demonstrating the device's suitability for its intended use, even if they are for a physical device rather than an AI/ML algorithm.

Here's the information that can be extracted, framed to best fit your request:

Acceptance Criteria and Study for the IOB Temperature Management System (as applicable to a physical thermal regulating device)

Since the IOB Temperature Management System is a physical device (a thermal regulating system) and not an AI/ML powered diagnostic or assistive technology, the typical "acceptance criteria" and "study" framework for AI/ML performance metrics (like sensitivity, specificity, AUC, etc.) and related study design details (sample size for test/training, ground truth methods, expert adjudication, MRMC) does not apply.

Instead, the provided document outlines the general "Safety and Performance Characteristics" and their verification methods to demonstrate substantial equivalence to a predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Not applicable / Not specified in the provided document for the types of tests described (temperature uniformity, accelerated stability, electrical safety, software validation, biocompatibility). These tests typically involve a defined number of units or samples under specific conditions rather than patient "test sets" as understood for AI/ML evaluation.

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

• Not applicable / Information not provided. The ground truth for these device performance tests is based on objective measurements and established standards (e.g., precise temperature readings, material degradation, electrical standards, ISO biocompatibility standards) rather than expert consensus on diagnostic interpretations.

4. Adjudication method for the test set

• Not applicable / Information not provided. Adjudication methods are not relevant for these types of engineering and material performance tests.

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 physical device, not an AI/ML diagnostic. A MRMC study is not relevant here.

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

• No. This is a physical device, not an AI/ML algorithm.

7. The type of ground truth used

• For Temperature Uniformity: Objective physical measurements against a standard for thermal performance (implied).
• For Shelf-Life: Objective laboratory testing for material degradation and functional integrity over time (accelerated aging).
• For Electrical Safety/EMC: Compliance with international safety standards (IEC60601-1, IEC 60601-1-2) through objective measurements.
• For Software Validation: Verification against design specifications and functional requirements.
• For Biocompatibility: Adherence to ISO 10993 standards (cytotoxicity, irritation, sensitivity) through laboratory testing.

8. The sample size for the training set

• Not applicable. There is no "training set" in the context of an AI/ML algorithm for this physical device.

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

• Not applicable. There is no "training set" or corresponding ground truth establishment mentioned for this device.

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The IOB Disposable Speculum is used to dilate the vagina and expose the interior of the vagina and the exterior of the cervix during pelvic examinations and other gynecologic procedures. It may be used with or without a removable light source.

The IOB disposable vaginal speculum consists of up and under plastic blades and handle with three different sizes (smail, medium and large). The speculum is used by medical professionals to visualize interior of vagina and cervix during patient examination.

The provided 510(k) summary does not contain the level of detail typically found in a clinical study report for AI/CADe devices. This device is a disposable speculum, a physical medical instrument, not an AI/CADe system. Therefore, the information requested about acceptance criteria, device performance, sample sizes, ground truth establishment, expert adjudication, and MRMC studies is not directly applicable in the same way it would be for a software-based diagnostic tool.

However, I can extract the relevant information regarding performance and acceptance based on the content available for this physical device.

1. Table of Acceptance Criteria and Reported Device Performance

For this physical device, acceptance criteria relate to its physical properties, manufacturing, and biological safety, rather than diagnostic accuracy metrics like sensitivity or specificity. Performance is primarily about functionality and equivalence to a predicate device.

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

This information is not applicable and not provided in the document. The device is a physical speculum; its testing involved "bench testing" and "stability study" simulating usage, not a clinical "test set" with patient data in the typical sense of a diagnostic algorithm.

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)

This is not applicable and not provided. "Ground truth" in the context of this device's testing would relate to physical performance metrics (e.g., structural integrity, ease of use), not diagnostic interpretation by medical experts.

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

This is not applicable and not provided. Adjudication methods are relevant for resolving discrepancies in expert interpretations of diagnostic data, which is not what was performed for this physical 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

This is not applicable. An MRMC study is relevant for evaluating the impact of AI/CADe systems on human reader performance for diagnostic tasks. This device is a physical instrument, not an AI/CADe system.

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

This is not applicable. This device is a physical speculum and does not involve an algorithm.

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

For this device, the "ground truth" for performance would likely be based on:

• Biocompatibility Standards: Adherence to ISO 10993 standards.
• Engineering Specifications: Meeting pre-defined physical strength, flexibility, and dimensional requirements.
• Predicate Device Comparison: Functional equivalence observed during simulated usage against the predicate device.

8. The sample size for the training set

This is not applicable. The concept of a "training set" refers to data used to train an AI algorithm. This device is a physical instrument.

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

This is not applicable, as there is no training set for a physical device.

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