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TechLive is a software application intended to provide remote access for real-time image acquisition, assistance, review, monitoring and standardization of imaging devices across multiple locations. It is a vendor neutral solution allowing read-only or full access control to connected devices. TechLive is also intended for training of medical personnel working on medical imaging devices. TechLive is not intended for diagnostic use.

TechLive is a software application intended to provide remote access for real-time image acquisition, assistance, review, monitoring and standardization of imaging devices across multiple locations. It is a vendor neutral solution allowing read-only or full access control to connected devices. TechLive is also intended for training of medical personnel working on medical imaging devices. TechLive is not intended for diagnostic use.

Clinical users can remotely access imaging devices from a computer via a secure software connection that streams video and audio, including access to keyboard and mouse controls. This setup allows remote users to assist local in-suite assistants or other clinical users by means of audio/video connection or perform remote acquisitions themselves. Depending upon the device used to acquire the images, the remote access can allow for "view mode", to support the in-suite assistant, or "control mode", where the remote user controls the console software of the imaging device. Remote access to the local imaging device can only be granted by the local in-suite assistant and can be granted or revoked as needed using an on-premises computer installed with the assistance touch interface. "Control mode" access may be granted on-demand or prior to acquisition to access the scanner. TechLive offers a secure collaboration platform with live audio and video, enabling remote acquisition and seamless collaboration among healthcare professionals.

TechLive is vendor-neutral and compatible with existing imaging devices, including Ultrasound (US), Magnetic Resonance Imaging (MRI), Computer Tomography (CT), and Positron Emission Tomography (PET/CT).

The provided FDA 510(k) clearance letter for DeepHealth, Inc.'s TechLive device does not contain the specific acceptance criteria or detailed study results related to numerical performance metrics. The document primarily focuses on establishing substantial equivalence to a predicate device, outlining the device's intended use, technological characteristics, and a summary of non-clinical testing performed.

Based on the provided text, here's what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

This information is not explicitly provided in the document. The clearance letter states that "Verification and validation demonstrated that the TechLive software, as designed and implemented, meets all pre-defined performance specifications, user needs and its intended use," but it does not list these specific performance specifications or their corresponding results in a quantified manner.

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

This information is not explicitly provided in the document. The text mentions "Verification and validation testing" and "Usability Studies" but does not detail the sample sizes for these tests or the provenance of any data used. Given the device is for remote access and not diagnostic use, it's possible the "test set" might refer to testing with various imaging devices and configurations, rather than a dataset of patient images.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not explicitly provided in the document. Since the device is "not intended for diagnostic use," the concept of "ground truth" related to medical diagnosis as established by experts would likely not apply in the traditional sense for direct performance evaluation. The "ground truth" for this device would more likely be related to the successful operation of remote access, control, and communication functionalities.

4. Adjudication Method for the Test Set

This information is not explicitly provided in the document.

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

A MRMC comparative effectiveness study was not conducted and is not applicable for this device. The document explicitly states: "TechLive is not intended for diagnostic use." MRMC studies are typically performed to assess the diagnostic performance of a device when used by multiple readers across various cases, often comparing it to human performance with or without AI assistance for diagnostic tasks. Since TechLive is for operational support and remote collaboration, not diagnosis, such a study would not be relevant.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study in the context of diagnostic accuracy was not conducted and is not applicable for this device. Again, the device is not intended for diagnostic use. The non-clinical verification and validation testing would have assessed the standalone functional performance of the software (e.g., successful remote connection, video/audio quality, control fidelity, security), but not diagnostic performance.

7. Type of Ground Truth Used

The type of "ground truth" used for this device would likely relate to objective measures of functional performance, system integration, and user interaction, rather than clinical outcomes or pathology. Examples of "ground truth" would be:

• Successful establishment and maintenance of remote connection.
• Accurate and responsive remote control of imaging devices.
• Clear and synchronized audio/video communication.
• Successful completion of tasks during usability testing.
  However, the document does not explicitly state the specific ground truths used for their non-clinical tests.

8. Sample Size for the Training Set

This information is not explicitly provided in the document. As TechLive is a software application for remote access and control, it may not involve a "training set" in the traditional machine learning sense for diagnostic image analysis. If it uses AI components for other functionalities (e.g., adaptive streaming), this information is not disclosed.

9. How Ground Truth for the Training Set Was Established

This information is not explicitly provided and is likely not applicable or detailed given the stated purpose of the device.

Summary of Device Acceptance Criteria and Study Information from the Document:

Given the lack of specific numerical performance data, the "acceptance criteria" can be inferred from the stated purpose and the type of testing performed, rather than quantified metrics.

Study Information:

• Clinical Testing: None performed.
• Non-Clinical Verification and Validation Testing: Conducted to demonstrate meeting pre-defined performance specifications, user needs, and intended use. Included functional, long-duration, and interoperability tests.
• Usability Studies (Human Factors): Conducted (Formative and Summative testing) to demonstrate safe and effective performance of critical tasks.
• Vendor Neutrality and Multi-Vendor Validation Testing: Performed to confirm interoperability across various scanner types and manufacturers.

Missing Key Information (Relevant to the questions asked):

• Specific, quantified acceptance criteria for functional performance (e.g., latency, video resolution, control responsiveness).
• Numerical results of performance testing against any defined criteria.
• Sample sizes for non-clinical verification and validation testing, and usability studies.
• Data provenance for any test data.
• Details on "ground truth" establishment for these functional tests (e.g., how "seamless console operation" was objectively measured and verified).
• Any information regarding training sets or AI model performance, as the device's primary function is remote access and not diagnostic AI.

In summary, the provided document focuses on regulatory compliance through substantial equivalence and adherence to standards for software development, risk management, and cybersecurity, rather than detailed quantitative performance metrics typically seen for diagnostic AI products.

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