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CARDIOVIEW™ 3000 interpretive software is a Windows-based program intended to interpret electrocardiograms. CARDIOVIEW™ 3000 interpretive software receives, displays and stores a single or standard 12-lead simultaneous ECG recording, which is transmitted either locally or transtelephonically from a Micromedical™ ECG monitor using a proprietary digital data transmission protocol. The device contains proprietary software algorithms to receive, store, analyze, and interpret the ECG signal.

The proposed device is computer software which receives, displays and stores a single or standard 12 Lead Simultaneous ECG recording, which is transmitted either locally or transtelephonically from a Micromedical™ ECG monitor using a proprietary digital data transmission protocol. Using a complex mathematical analysis of a 12 Lead ECG, the software can also provide an interpretation of the ECG recording.

The provided text describes the CARDIOVIEW™ ECG Interpretive Software, K974352. However, it does not include detailed information regarding specific acceptance criteria, a comprehensive study comparing the device to acceptance criteria, sample sizes for test or training sets, expert qualifications, or adjudication methods.

The document is a 510(k) summary and an FDA clearance letter. It states that nonclinical testing was performed to compare the proposed device to a predicate device (MAX 1 Exercise Testing System), and concluded that the proposed device is "substantially equivalent" to the predicate device. Substantial equivalence is the basis for 510(k) clearances, implying that the new device is as safe and effective as a legally marketed predicate device.

Therefore, many of the requested details are not present in this document.

Here's a summary of what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: Specific quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy targets for ECG interpretation) are not detailed in this document.

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

Missing Information: The document does not specify the sample size of the test set used for nonclinical testing. It also does not mention the data provenance (e.g., country of origin, retrospective or prospective nature of the data).

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

Missing Information: The document does not mention the number or qualifications of experts used to establish ground truth for any testing.

4. Adjudication method for the test set

Missing Information: No adjudication method is described.

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

Missing Information: The document does not describe a multi-reader, multi-case comparative effectiveness study involving human readers with and without AI assistance. The nonclinical testing mentioned was a comparison between the proposed device and a predicate device.

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

Answer: Yes, the nonclinical testing section states: "Testing showed the proposed device to be substantially equivalent to the predicate device. Both devices use proprietary algorithms to receive, store, analyze and interpret the ECG signal." This implies a standalone evaluation of the algorithm's performance against the predicate device's algorithm.

7. The type of ground truth used

Missing Information: The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). In the context of ECG interpretation, ground truth is typically established by expert cardiologists reviewing the ECGs and, sometimes, correlating with clinical data or more definitive diagnostic tests.

8. The sample size for the training set

Missing Information: The document does not provide any details about a training set or its size.

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

Missing Information: As no training set details are provided, the method for establishing its ground truth is also not mentioned.

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The Micromedical™ 12 Lead Simultaneous Cable is intended for use in acquiring a patient ECG signal via 10 leads connected to the patient's chest, converting the ECG patient DOO siguir 11-2-2, and transferring this information to a Micromedical™ monitor using a proprietary digital data transfer protocol.

The proposed device is a 12 Lead Simultaneous Cable to connect electrodes to an electrocardiograph or to a Micromedical™ monitor.

The provided text does not contain detailed information about specific acceptance criteria and a study proving the device meets them in the way described in the prompt's request. The document is a 510(k) summary for a 12-Lead Simultaneous Cable, focusing on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with detailed metrics against pre-defined acceptance criteria.

However, I can extract the available information and highlight what is missing based on your request.

Missing Information:

The provided text does not include the following details that are typically found in a detailed performance study:

• A table of specific acceptance criteria (e.g., signal-to-noise ratio, frequency response, accuracy of parameter measurements).
• Reported device performance against those specific criteria.
• Sample size used for a test set (beyond "non-clinical testing").
• Data provenance (country of origin, retrospective/prospective).
• Number of experts or their qualifications for ground truth establishment.
• Adjudication method for a test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, or any effect size of AI assistance on human readers.
• Specific details of a standalone (algorithm only) performance study.
• The specific type of ground truth used (e.g., expert consensus, pathology, outcomes data).
• Sample size for the training set.
• How ground truth for the training set was established.

Based on the available text, here's what can be inferred/extracted:

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

The document states: "Non-clinical testing was performed to compare the device to the predicate device. Testing showed the proposed device to be substantially equivalent to the predicate device."

• Acceptance Criteria (Inferred): Substantial equivalence to the predicate device (MAX 1 Exercise Testing System) regarding its function of acquiring and transmitting ECG signals. The specific quantitative criteria for this equivalence are not detailed.
• Reported Device Performance: The device was found to be "substantially equivalent" to the predicate device. No specific numerical performance metrics are provided.

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

• Test Set Sample Size: Not specified. The document only mentions "Non-clinical testing."
• Data Provenance: Not specified.

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

• Not applicable as no specific human expert review for establishing ground truth is mentioned for performance evaluation. The comparison is against a predicate device's expected performance.

4. Adjudication method for the test set:

• Not applicable/Not specified, as no human expert review process is 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, this type of study was not mentioned. The device is a cable for acquiring and transmitting ECG signals, not an AI-powered diagnostic tool.

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

• The device itself is a physical cable. Its "performance" would be related to signal integrity and transmission accuracy, which were presumably assessed in non-clinical standalone tests, but details are not provided. There's no AI algorithm involved.

7. The type of ground truth used:

• The ground truth implicitly used is the performance of the legally marketed predicate device (MAX 1 Exercise Testing System), against which the new device demonstrated "substantial equivalence." The specific metrics from the predicate device that served as ground truth are not detailed.

8. The sample size for the training set:

• Not applicable. The device is a physical cable, not a machine learning model that requires a training set.

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

• Not applicable.

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The Biolog™ 3000 electrocardiograph detects an ECG using a single lead patient cable or alternatively can receive ECG data detected by the Micromedical™ 12 Lead Simultaneous Cable. The Biolog™ 3000 electrocardiograph can record the ECG, display the ECG signal on a built-in LCD screen, and download the recorded ECG data to a PC running CardioView™ 3000 software or to the Micromedical™ Printer Interface. The device contains proprietary software algorithms to detect an ECG signal or receive ECG data from a patient cable, remove unwanted interference from the ECG signal, store the signal into memory, and download it to peripheral devices.

The proposed device is an electrocardiograph that can record the ECG, display the ECG signal on a built-in LCD screen, and download the recorded ECG data to a PC running Cardio View7M 3000 software or to a Micromedical™ monitor to display the ECG signal on a personal computer. The device includes a Biolog™ 3000 unit, a User's Manual, and accessories.

This 510(k) summary for the Biolog™ 3000 electrocardiograph does not contain detailed acceptance criteria or a study proving the device meets those criteria. The provided text is a summary of the 510(k) submission, focusing on establishing substantial equivalence to a predicate device.

Here's an breakdown of the requested information based on the provided text, and where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document only mentions "Nonclinical testing was performed to compare the device to the predicate device."

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• MRMC Study Done: No, an MRMC study is not mentioned as having been performed. The safety and effectiveness are established through substantial equivalence to a predicate device based on nonclinical testing.
• Effect Size of Human Readers Improvement with AI vs. without AI: Not applicable, as no MRMC study or AI assistance aspect is mentioned.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study Done: Yes, in a limited sense. The "Nonclinical testing" conducted appears to be a standalone evaluation of the device's technical performance against the predicate. However, detailed metrics of this performance are not provided. The statement "The device contains proprietary software algorithms to detect an ECG signal or receive ECG data from a patient cable, remove unwanted interference from the ECG signal, store the signal into memory, and download it to peripheral devices" implies algorithm functionality was tested.

7. Type of Ground Truth Used

• Type of Ground Truth: Not explicitly stated. Given it's an ECG device, the "ground truth" for nonclinical testing would likely be derived from a controlled signal generator or established reference ECG readings, used to confirm the device's ability to accurately detect, process, and display ECG signals compared to the predicate device.

8. Sample Size for the Training Set

• Training Set Sample Size: Not specified. The document does not explicitly mention a training set, which would typically be associated with machine learning or AI models undergoing supervised training. While the device contains "proprietary software algorithms," the documentation doesn't detail their development or training methodology.

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

• Ground Truth Establishment for Training Set: Not specified, as a training set is not explicitly mentioned.

Summary of Information Provided:

The 510(k) summary for the Biolog™ 3000 electrocardiograph primarily focuses on establishing "substantial equivalence" to a predicate device (MAX 1 Exercise Testing System) through "nonclinical testing." It does not provide specific details on acceptance criteria, test set specifics (sample size, data provenance), expert involvement, adjudication methods, or the results of detailed performance studies as would be expected for an AI/ML-based device with comprehensive performance claims. The "proprietary software algorithms" are mentioned for detecting, filtering, storing, and downloading ECG data, but their validation process in terms of statistical metrics or clinical studies is not elaborated upon in this summary.

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The Micromedical Printer Interface is used to download ECG data from a Micromedical ECG monitor and print ECG recordings on standard letter-sized paper by using one of a number of standard commercially available Canon or Hewlett Packard ink jet printers.

The Micromedical Printer Interface receives data from a Micromedical ECG monitor and transmits it through a parallel cable to one of a number of commonly available Canon or H-P bubble jet printers to print the ECG tracing on standard-sized paper.

This 510(k) pertains to a hardware device (Printer Interface) rather than an AI/ML powered software device. Therefore, the requested information regarding acceptance criteria, study details, and ground truth establishment, which are typical for AI/ML device evaluations, are not applicable here.

The provided document describes the Micromedical Printer Interface as a device that receives data from a Micromedical ECG monitor and transmits it to a standard ink jet printer to print ECG tracings. The basis for clearance is substantial equivalence to an existing predicate device, the Ralin CorFax.

Here's why the AI/ML-specific questions are not applicable:

• Device Type: This is a hardware interface for printing, not an algorithm or software that processes or interprets medical data.
• Substantial Equivalence: The clearance is based on comparing the new device to a legally marketed predicate device, demonstrating that it's as safe and effective. This typically involves performance bench testing, electrical safety, EMC testing, and ensuring the output is clinically equivalent to the predicate, rather than clinical studies with human readers or specific statistical performance metrics against a ground truth as would be done for an AI/ML algorithm.
• Lack of AI/ML Component: The submission explicitly mentions "proprietary algorithms to receive the data from ECG monitors and transmit it to a printing device," but this refers to the internal software/firmware necessary for device function (e.g., data formatting, communication protocols), not AI/ML algorithms for medical diagnosis or interpretation.

Therefore, the requested table and detailed study information for AI/ML devices cannot be extracted from this 510(k) submission.

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CardioView is a computerized, enhanced electronic Transtelephonic System designed for clinical indications to allow physicians or other health care providers to remotely view and analyze patient ECG data. This system is suited for small to medium health care monitoring facilities. If offers a 12 lead ECG remote monitoring system which is more comprehensive than conventional single lead transtelephonic Software.

CardioView is a computerized, enhanced electronic Transtelephonic System designed for clinical indications to allow physicians or other health care providers to remotely view and analyze patient ECG data. This system is suited for small to medium health care monitoring facilities. If offers a 12 lead ECG remote monitoring system which is more comprehensive than conventional single lead transtelephonic Software. Both devices use a remote user input device that retains the ECG signal and transmits it over the telephone lines. Both devices can use a switched telephone network. Both devices use a modern at the Host site to communicate with the remote device and uplink the data into the Computer. Both devices use a DOS based Computer which runs in Windows "" to display data. Both devices: output a display that resembles a conventional ECG display. Both devices retain a electronically stored sample. Both act on that sample using mathematical computations. Both use a proprietary algorithm. Both use computer programming in a Windows "" environment.

This K955891 filing for the CardioView Transtelephonic Software, Part Number 268-400-004, is a 510(k) premarket notification. In this type of submission, the primary goal is to demonstrate substantial equivalence to a predicate device, not necessarily to independently prove the device meets specific performance acceptance criteria through a dedicated study.

Therefore, the provided text does not contain the detailed information requested about acceptance criteria, a specific study proving those criteria, or the methodology for ground truth establishment, sample sizes for training/test sets, or MRMC studies.

The document focuses on comparing the CardioView to its predicate device, CardioMagic™ Software (K925639), to establish that it is as safe and effective as the already marketed device.

Here's a breakdown of why each section of your request cannot be fully answered from the provided text:

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

• Acceptance Criteria: Not explicitly stated as quantifiable metrics. The "acceptance criteria" for a 510(k) submission are generally that the device is "as safe and effective" as the predicate device.
• Reported Device Performance: Instead of specific performance metrics, the document lists functional similarities to the predicate device. These are qualitative comparisons rather than quantitative performance results.

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

• Not provided. There is no mention of a specific test set, its size, or its provenance. The demonstration of substantial equivalence relies on functional and technological comparison.

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/Not provided. Since there's no described test set with independently established ground truth, this information is absent. The "ground truth" for a 510(k) is implicitly the established safety and effectiveness of the predicate device.

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

• Not applicable/Not provided. No test set or independent adjudication process is 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 was done or mentioned. CardioView is described as a "computerized, enhanced electronic Transtelephonic System" to "remotely view and analyze patient ECG data," implying it's a tool for physicians, but not an "AI assistance" in the modern sense that would typically warrant an MRMC study comparing human performance with and without AI. Its function is to facilitate viewing and analysis, not to interpret or diagnose.

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

• Not explicitly described as a standalone study. While the device uses a "proprietary algorithm" and performs "mathematical computations," its purpose is to "allow physicians or other health care providers to remotely view and analyze patient ECG data." This implies human-in-the-loop use. The document doesn't present an evaluation of the algorithm's performance in isolation from a human user.

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

• Not applicable/Not provided in the traditional sense. For a 510(k), the "ground truth" is established by showing that the new device functions similarly to and is as safe and effective as the predicate device, which is already legally marketed. There isn't an independent "ground truth" for ECG interpretation specifically detailed in this document for CardioView.

8. The sample size for the training set

• Not provided. No training set is mentioned as this is a 510(k) based on substantial equivalence, not a de novo clearance requiring extensive performance data from an AI/ML model trained on a dataset.

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

• Not applicable/Not provided. No training set or ground truth establishment for it is mentioned.

Summary of what the document does provide regarding "acceptance" and "proof":

The document aims to demonstrate that CardioView meets the criteria for substantial equivalence to CardioMagic™ Software (K925639). The "proof" is presented through a series of direct comparisons on various aspects:

• Intended Use: Both are for clinical applications allowing physicians to remotely view and analyze ECG data.
• Technology & Functionality:
  • Both use a remote user input device to transmit ECG signals over telephone lines.
  • Both can use a switched telephone network.
  • Both use a modem at the host site to communicate and uplink data.
  • Both use a DOS-based computer running Windows for data display.
  • Both output a display resembling a conventional ECG.
  • Both retain electronically stored samples.
  • Both act on samples using mathematical computations.
  • Both use a proprietary algorithm.
  • Both use computer programming in a Windows environment.
• Limitations: Neither claims to be laboratory analysis equipment; both are for remote convenience and easy response.
• Design & Manufacturing: CardioView conforms to Good Manufacturing Procedures.
• Safety & Effectiveness: MICROMEDICAL INC. states that the device is "safe and effective for the application for which it is intended and has been tested to confirm safety and efficacy." They also maintain an in-house reporting system for adverse events.

Essentially, the "study" is the comparison of the new device's specifications and functionality against a legally marketed predicate device to argue that it does not raise new questions of safety or effectiveness.

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