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The Midmark IQecg is indicated for use, under the supervision of a Physician, to obtain electrocardiograms from the adult and pediatric human body surface. The process of taking an electrocardiogram is non-invasive, painless, without direct risk to the patient and is reproducible.

The Midmark IQecg is a PC based 12-lead resting diagnostic electrocardiograph with interpretation and data storage capabilities. Together with the Midmark IQmanager software running on Microsoft Windows operating systems, the IQecg device can acquire 12-lead ECG (electrocardiogram) data, generate ECG measurement and interpretation results, provide review/edit functions to modify the measurement and interpretation results, store the ECG data and report in a database, archive the ECG reports for future reference and share the ECG reports with other physicians via network or email. The IQecg can also be connected to servers and electronic medical records.

The provided document is a 510(k) Pre-market Notification for the Midmark IQecg, a resting diagnostic electrocardiograph. It details the device description, technological comparison to a predicate device, intended use, and general performance testing. However, it does not contain detailed information regarding specific acceptance criteria, a comprehensive study proving the device meets those criteria, or the methodology typically associated with AI/ML device studies (e.g., ground truth establishment, sample sizes for training/test sets, expert adjudication, MRMC studies).

The document is a regulatory submission for a traditional medical device, not an AI/ML powered device, which would typically involve different types of performance testing and reporting for its interpretative algorithms. The "interpretation" provided by the IQecg is likely based on established, rule-based algorithms for ECG analysis, rather than a machine learning model.

Therefore, many of the requested data points (like sample sizes for test/training sets, detailed ground truth establishment, expert adjudication, MRMC studies, or standalone performance for an AI algorithm) are not explicitly available or applicable in this document.

1. Table of Acceptance Criteria and Reported Device Performance

The document states that "The Midmark IQecg was tested in accordance with requirements and procedures, and test results indicated that the device complies with the predetermined requirements." However, the specific acceptance criteria and detailed quantitative performance metrics are not provided in this summary. The comparison focuses on technological characteristics rather than clinical performance metrics or specific algorithm accuracy.

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions "Performance Testing" was conducted, but details are absent.

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

Not applicable/Not specified. For this type of traditional ECG device with established interpretation algorithms, ground truth for performance testing is typically based on standardized databases or reference ECG recordings with known arrhythmias/morphologies, rather than expert consensus on individual cases for algorithm validation as would be common for new AI/ML systems.

4. Adjudication method for the test set

Not applicable/Not specified.

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 predates the widespread use of sophisticated AI for ECG interpretation requiring such studies in regulatory submissions. The interpretation component is likely based on established, rule-based algorithms, not a novel AI model that would assist human readers in an MRMC study.

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

The device is described as having "interpretation results." While the performance of this interpretation algorithm was likely assessed, the specifics of this "standalone" performance testing (e.g., metrics like sensitivity, specificity for various conditions) are not detailed in the provided summary. The comparison focuses on hardware specifications and QTc calculation methods, implying that the interpretation algorithm itself is substantially equivalent to the predicate.

7. The type of ground truth used

Not specified. For ECG interpretation algorithms, ground truth often comes from:

• Standardized ECG databases (e.g., MIT-BIH Arrhythmia Database).
• Clinically adjudicated ECGs (though details of adjudication would be needed).
• Correlation with other diagnostic tests or clinical outcomes.
  Given this is a traditional ECG device, it's highly probable it relies on established benchmarks.

8. The sample size for the training set

Not applicable/Not specified. For traditional rule-based algorithms, there isn't a "training set" in the machine learning sense. If the interpretation component involved statistical models, the data used to develop them is not mentioned.

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

Not applicable/Not specified, as it's not an AI/ML device with a training set.

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The IQvitals and IQvitals System is intended to be used by clinicians and medically qualified personnel for measuring adult and pediatric patients for noninvasive blood pressure, pulse rate, noninvasive functional oxygen saturation of arterial hemoglobin (SpO2), temperature and weight.

Patient information such as name, age, height, pain score etc. can be entered manually.

The IQvitals and IQvitals System are patient monitors intended to be used by clinicians and qualified medical personnel for spot check monitoring of noninvasive blood pressure (NIBP), pulse oximetry (SpOz), temperature and for the IQvitals device, weight.

Patient Record information, such as height, respiration rate and pain level, can be manually entered by clinicians via the user interface.

The provided text describes a medical device, the IQvitals and IQvitals System, and its substantial equivalence determination by the FDA. However, it does not contain any information about acceptance criteria or a specific study proving the device meets those criteria, as understood in the context of an AI/ML medical device.

Here's why and what information is available:

The document is a 510(k) summary for a "Patient Physiological Monitor." This type of device relies on established physiological measurement principles, not AI/ML algorithms. The performance testing described is focused on validating the accuracy and reliability of these standard physiological measurements against established norms and a predicate device.

Therefore, many of the requested points, such as "sample size used for the test set," "number of experts used to establish ground truth," "adjudication method," "MRMC study," "standalone performance," and "training set details," are not applicable to this document as it pertains to the evaluation of an AI-powered medical device.

Here's a breakdown of what information can be extracted or inferred from the provided text, and where the requested information is absent:

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

• Acceptance Criteria: Not explicitly stated as pass/fail numerical targets in the provided text. The general acceptance criterion is "substantially equivalent" to the predicate device. For specific parameters, compliance with "requirements and procedures" and "standards" is mentioned.
• Reported Device Performance:

  Parameter	Reported Performance
  Non Invasive Blood Pressure (NIBP)	Tested in accordance with requirements and procedures; results indicated compliance with predetermined requirements and substantial equivalence to the predicate.
  Temperature	Tested in accordance with requirements and procedures; results indicated compliance with predetermined requirements and substantial equivalence to the predicate.
  SpO2	Tested in accordance with requirements and procedures; results indicated compliance with predetermined requirements and substantial equivalence to the predicate.
  Pulse Rate	Tested in accordance with requirements and procedures; results indicated compliance with predetermined requirements and substantial equivalence to the predicate.
  Display	Tested or evaluated.
  Electrical	Tested or evaluated.
  Environmental	Tested or evaluated.
  Software	Tested or evaluated.
  Biocompatibility	Tested or evaluated.

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

• Sample Size: Not specified.
• Data Provenance: Not specified. (The context strongly suggests physiological measurements, likely from human subjects, but details are not provided).

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

• Not Applicable. This is not an AI/ML device requiring expert ground truth for image interpretation or similar. The "ground truth" for physiological measurements would typically be established by validated reference instruments or methods.

4. Adjudication method for the test set

• Not Applicable. Not an AI/ML device seeking consensus on interpretations.

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 not an AI-assisted interpretation device. The study type would be a typical performance validation study for a medical monitor.

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

• Not Applicable. This device is a physiological monitor, not an AI algorithm. Its performance is its "standalone" output of physiological parameters.

7. The type of ground truth used

• The "ground truth" for physiological measurements would involve reference standards or established, validated methods for measuring NIBP, temperature, SpO2, and pulse rate (e.g., invasive blood pressure monitoring for NIBP accuracy, reference thermometers, co-oximeters for SpO2 calibration). These are implied by the statement "tested in accordance with requirements and procedures, and test results indicated that the device complies with the predetermined requirements."

8. The sample size for the training set

• Not Applicable. This device does not use a training set in the context of AI/ML.

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

• Not Applicable. This device does not use a training set in the context of AI/ML.

Study Information (General)

The study described is a performance testing and comparison to a predicate device to establish substantial equivalence.

• Study Type: Non-clinical areas thoroughly tested or evaluated against "standards and the predicate." This implies a series of bench tests, simulations, and likely human clinical studies (though details are not provided) to measure accuracy, precision, and reliability of the physiological measurements.
• Predicate Device: Well@Home System (K040012).
• Conclusion: "Based upon a comparison of devices and performance testing results, the IQvitals and IQvitals System is substantially equivalent to the predicate device."

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IQmark EZ Stress is intended to be used under the supervision of a physician, in hospitals, clinics and physician's office, to acquire, display, process, record, analyze and print the patient's electrocardiograms from the human body surface during stress induced from exercise devices such as a treadmill, a bicycle ergometer or drug induced (pharmacological) stress.
The device may provide interfaces with external devices, such as a treadmill or an ergometer, non-invasive blood pressure equipment, and computer communication equipment.
The device is not intended to be used as a vital signs physiological monitor.

The IQmark EZ Stress test system is a computer-based diagnostic electrocardiograph that is designed for exercise stress test. The IQmark stress runs on the Microsoft Windows environments and can control a treadmill or an ergometer through a serial port. The IQmark EZ Stress provides real time ECG data acquisition, waveform display, and ORS detection. It calculates the heart rate, detects ventricular ectopic beats, generates the average beats, measures the ST segment levels and slopes, generates the test reports, and stores the reports in the database. The IQmark EZ Stress system also provides reports and FCG strip printing and review and editing capabilities for trained personnel to manage the patient`s report.

Here's an analysis of the acceptance criteria and study information based on the provided text for the IQmark EZ Stress device:

Acceptance Criteria and Study Details for IQmark EZ Stress

This 510(k) submission primarily relies on demonstrating substantial equivalence to predicate devices, rather than establishing novel performance metrics. Therefore, the "acceptance criteria" for the IQmark EZ Stress are largely defined by its ability to meet the same technical specifications and features as the predicate devices and conform to relevant industry standards.

1. Table of Acceptance Criteria and Reported Device Performance

Since this submission focuses on substantial equivalence, the "acceptance criteria" are implied by the comparison to predicate devices and adherence to standards. The "reported device performance" is described as meeting these criteria.

• ECG frequency response (-3 dB): 0.05-150Hz
• High pass filter: 0.05Hz
• Low pass filter: 40, 150Hz
• Line Filter: 50, 60Hz
  (Matches or is comparable to predicate devices where specified). |
  | Conformance to AAMI/ANSI EC11: 1991 (ECG hardware). | ECG hardware is designed in conformance with AAMI/ANSI EC11: 1991. |
  | Meeting EMC requirements of EN60601-1-2:2001. | ECG hardware meets the EMC requirements of EN60601-1-2:2001. |
  | Performance of Heart Rate Calculation and ST Segment Measurements according to AAMI/ANSI EC13: 1992 and AAMI/ANSI EC38: 1998. | Performance of heart rate calculation and ST segment measurements tested according to appropriate sections of AAMI/ANSI EC13: 1992 and AAMI/ANSI EC38: 1998. |
  | Software meets design specifications and user-level requirements. | Software Verification Procedure executed to confirm correct implementation of design. Software Validation Procedure executed to challenge completeness and correctness of user-level requirements. |
  | Implementation of risk reduction activities identified in System Risk Analysis. | Traceability Analysis demonstrated implementation of prescribed risk reduction activities. |
  | Safe and Effective as predicate devices. | Test results demonstrated the device is as safe and effective as the two predicate devices. |

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

The document does not specify a distinct "test set" with a particular sample size for external clinical data. Instead, the validation primarily relies on:

• Internal Verification & Validation Tests: These were performed for the "entire development effort" and for "user level requirements" but no specific case numbers are provided.
• Beta Tests: The device underwent "beta tests in a physician's office." No sample size or data provenance (e.g., country of origin, retrospective/prospective) for these beta tests is explicitly stated.

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

Not applicable. The document does not describe the establishment of a "ground truth" by experts for an external test set in the conventional sense of a clinical study. The validation relies on internal testing against design specifications, compliance with industry standards, and comparison to predicate devices, implying that the "ground truth" for these tests would be the expected output based on these specifications and standards.

4. Adjudication Method for the Test Set

Not applicable. No external test set requiring expert adjudication is described in the provided text.

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 comparative effectiveness study is mentioned. This device is a stress test system, not an AI-powered diagnostic reader, so such a study would not be directly applicable in the context of human reader improvement.

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

Yes, aspects of algorithm-only performance were tested:

• The QRS detection, heart rate calculation, and ST segment measurement algorithms (derived from Brentwood's ST and Arrhythmia Analysis library) were tested according to the appropriate sections of AAMI/ANSI EC13: 1992 and AAMI/ANSI EC38: 1998. These are industry standards for ambulatory electrocardiographs and stress monitors, implying a standalone performance evaluation against defined criteria.

7. The Type of Ground Truth Used

The "ground truth" for the various tests mentioned appears to be:

• Industry Standards: For QRS detection, heart rate, and ST segment measurements (AAMI/ANSI EC13: 1992 and AAMI/ANSI EC38: 1998). These standards define expected performance characteristics and often include reference data or methods for assessing accuracy.
• Design Specifications: For the general software functionality and user-level requirements, the ground truth would be the documented design specifications and requirements.

8. The Sample Size for the Training Set

Not applicable. This document describes a traditional medical device (stress test system) whose algorithms are derived from an existing library (Brentwood's ST and Arrhythmia Analysis library, K013717). It does not mention machine learning or AI models requiring a "training set" in the modern sense.

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

Not applicable, as no training set for a machine learning model is mentioned.

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The intended use of the IQmark Digital Holter is for evaluation of the recorded ambulatory ECG for patients who need ambulatory monitoring, such as, but not limited to, those have complaints of chest pain, palpitations, dizziness, shortness of breath, or those have pacemaker implanted. The evaluation includes measurements and statistics of arrhythmia, R-R variability and ST segment changes in the recorded ECG data. The computer-generated results do not contain diagnostic interpretation, intended users are expected to review the report.

The IOmark Digital Holter is intended to be used only by physicians or on the order of a physician.

The intended use of the IOmark Digital Holter as described in its labeling has not changed from the cleared device, Rhythmscan Precision 6000 (K914577).

The IOmark Digital Holter is a software program that analyzes recorded ambulatory ECG (Holter) then creates statistical reports based on analyzed data. The ambulatory ECG, as well as pacemaker pulse detection data, is pre-recorded onto data storage mediums by Holter recorders. The IQmark Digital Holter software reads these raw data into computers then performs analysis to generate statistical reports.

The IQmark Digital Holter software provides review and editing tools that allow trained medical personnel to review and edit the initial analysis results to diagnose patients. The IQmark Digital Holter software does not provide diagnostic interpretation.

The IQmark Digital Holter software also provides statistical results of pacing events for pacemaker patients. Like other features in the software, Holter scanning operators can review and edit, if necessary, any analysis results.

The provided 510(k) summary for the IQmark Digital Holter (K031466) primarily focuses on demonstrating substantial equivalence to a predicate device (Rhythmscan Precision 6000, K914577), rather than presenting a detailed study with explicit acceptance criteria and performance data for the IQmark Digital Holter itself.

Therefore, many of the requested details about acceptance criteria, specific performance metrics, sample sizes, ground truth establishment, and expert involvement are not explicitly stated in the provided document. The 510(k) process for this device relies on the existing clearance of the predicate device and asserts that the changes in the IQmark Digital Holter do not alter the fundamental scientific technology or intended use.

Here's a breakdown of the available information based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria: The document does not explicitly state quantitative acceptance criteria for the IQmark Digital Holter's performance. The primary "acceptance" is based on demonstrating substantial equivalence to the predicate device, Rhythmscan Precision 6000 (K914577), by showing that its intended use and fundamental scientific technology have not changed.

Reported Device Performance: No specific quantitative performance metrics (e.g., sensitivity, specificity, accuracy for arrhythmia detection) are presented for the IQmark Digital Holter. The document states that "Both devices generate statistical results based on an identical set of analysis results" and that the modified software "has not changed the fundamental scientific technology of the device." This implies that the performance is considered equivalent to the predicate device without needing re-validation of specific metrics for the new device.

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

The document does not describe a distinct "test set" and corresponding sample size for evaluating the IQmark Digital Holter's performance as a standalone product. The submission relies on the substantial equivalence to the predicate device, implying that the predicate's performance, which was presumably validated using appropriate data, is considered applicable.

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

Not applicable, as a specific "test set" for the IQmark Digital Holter with associated ground truth established by experts is not described in this 510(k) summary. The document mentions that "intended users are expected to review the report" and "Physicians or scanning operators can use provided review and editing tools to verify ECG strips in all categories as well as their measurements and statistics," indicating that human expertise is part of the clinical workflow, but not establishing a ground truth for a performance study within this submission.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

Not applicable, as a specific "test set" requiring adjudication for ground truth establishment is not described.

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 is mentioned or implied. The device is described as an analysis software that provides statistical reports, which are then reviewed and edited by "trained medical personnel" or "physicians or scanning operators." It's not presented as an AI-powered diagnostic aid that improves human reader performance in a controlled study scenario. The core functionality is automated analysis followed by human review/editing.

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

While the device performs automated analysis and generates statistical reports, the document explicitly states:

• "The IQmark Digital Holter software does not provide diagnostic interpretation."
• "The computer-generated results do not contain diagnostic interpretation, intended users are expected to review the report."
• "Physicians or scanning operators can use provided review and editing tools to verify ECG strips in all categories as well as their measurements and statistics."

This strongly indicates that the device's performance is intended to be used with human-in-the-loop review and editing, and no standalone performance study without human intervention is described as part of this 510(k) submission.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

No specific ground truth type is mentioned because a dedicated independent performance study for the IQmark Digital Holter is not described. The presumption is that the predicate device's performance was established using appropriate ground truth, likely expert interpretation of ECGs, given the nature of Holter analysis.

8. The Sample Size for the Training Set

Not applicable. The document does not describe a machine learning algorithm or a "training set" in the context of this 510(k) summary. The device is a "software program that analyzes recorded ambulatory ECG (Holter)" and is based on the "fundamental scientific technology" of its predicate. This suggests a rule-based or conventional signal processing algorithm rather than a data-driven machine learning model requiring a training set.

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

Not applicable, as no training set or machine learning algorithm requiring such ground truth is mentioned.

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The intended user is a medical device manufacturer who will integrate the ST/AR Library into a computerized cardiac monitoring device. The ST/AR Library integrator will ultimately identify the indications for use, depending on the nature of their device.

The analysis capabilities of the ST/AR Library are indicated for monitoring and detecting the following from up to 12 body surface ECG leads for adult, pediatric, or neonatal patients:

• QRS detection
• ventricular ectopic beat detection (non-paced only)
• rhythm call analysis, including asystole, bigeminy, couplets, irregular heart rate, pause or missed beat, VEB/minute, run, trigeminy, triplets, ventricular tachycardia
• ST segment level measurement (adult patients only)
• ventricular fibrillation detection

The Brentwood Real Time ST and Arrhythmia Analysis Software Library is an "object library'. An object library is a collection of callable functions that have been compiled (or assembled) into the native machine code of the computer on which they will execute. An application software program can be written to invoke some or all of the functions in an object library. The compiled (or assembled) application code can be "linked" to the called functions from an object library at the time the executable code image is built. An executable code image created in this manner will contain the application software code and all of the functions it invoked from the object library.

The Brentwood Real Time ST and Arrhythmia Analysis Software Library consists of a collection of ANSI Standard C (ISO/IEC 9899) callable functions. It provides real time ECG signal processing, QRS detection, QRS complex feature extraction, ventricular ectopic beat detection, ST level measurement, rhythm calls, and ventricular fibrillation detection capabilities for up to 12 leads of captured ECG lead data.

Brentwood will compile the Brentwood Real Time ST and Arrhythmia Analysis Software Library using the compiler specified by an ECG analysis device manufacturer. An object library will be created and delivered to the manufacturer, who can then integrate it into application software for their ECG analysis device(s).

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that performance testing was conducted in accordance with ANSI/AAMI EC57:1998. This standard defines the acceptance criteria for these types of measurements. While the specific numerical acceptance criteria for each metric (e.g., QRS detection sensitivity/specificity, heart rate accuracy, VEB detection accuracy) are not explicitly stated in the provided text, the document implies that the device met these criteria by stating "The following testing was performed in accordance with ANSI/AAMI EC57:1998 to evaluate the performance of the Brentwood Real Time ST and Arrhythmia Analysis Software Library." and subsequently receiving FDA clearance.

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

• Sample Size for Test Set: Not explicitly stated as a number of patients or recordings. However, the study used the following standard databases:
  • AHA (American Heart Association) database
  • MIT-BIH Arrhythmia Database
  • NST (noise stress test) database
  • CU (Creighton University) database (for ventricular fibrillation specifically)
  • ESC (European Society of Cardiology) database (for ST segment analysis specifically)
• Data Provenance: Retrospective, as standard, publicly available databases (AHA, MIT-BIH, NST, CU, ESC) were utilized. The country of origin of these databases is generally international, with MIT-BIH being U.S.-based.

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

• Number of Experts: Not specified in the provided text.
• Qualifications of Experts: Not specified in the provided text. However, for established standard databases like MIT-BIH and AHA, the ground truth annotations are typically performed by experienced cardiologists or electrophysiologists.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified in the provided text. For established standard databases, the ground truth may have been generated through consensus or a "gold standard" based on expert review.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not performed. The testing focused on the standalone performance of the software library against established databases, not on comparing human readers with and without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Standalone Performance: Yes, a standalone performance evaluation was done. The entire performance testing section describes the evaluation of the "Brentwood Real Time ST and Arrhythmia Analysis Software Library" against standardized databases, focusing solely on the algorithm's capabilities.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth was based on expert annotations and established reference points within the standard databases (AHA, MIT-BIH, NST, CU, ESC). This can be classified as expert consensus/annotation-based ground truth, as these databases are meticulously reviewed and annotated by specialists.

8. The Sample Size for the Training Set

• Sample Size for Training Set: Not specified in the provided text. The document describes a "software library" that provides functions, implying it might be a predefined algorithm or model rather than something that was "trained" in the modern machine learning sense using a specific training set. If it was trained, the details are not provided.

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

• Ground Truth for Training Set: Not specified. As mentioned above, it's unclear if a traditional "training set" with established ground truth was used in the modern machine learning context for this software library. If it was, the method for establishing ground truth is not provided.

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