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The PCR Eleva System is a digital film processing system for reading and then digitizing X-ray images from reusable imaging plates which have been exposed in conventional radiographic examination devices. The digitized X-ray images can then be viewed, stored, post-processed and printed. The PCR Eleva system can be used in all conventional RAD/RF examination situations, except for mammography. PCR is suitable for routine RAD exams as well as specialist areas, like intensive care units, trauma departments and pediatric departments.

A PCR Eleva consists of one or more workspots with PCR Eleva Software and one or more image plate readers. All components are connected via standard ethernet. The system complies with the ACR/NEMA DICOM Version 3 Digital Image Communication in Medicine Standard. Imaging plates are exposed via conventional X-Ray devices. The imaging plates used in PCR systems are coated with a luminescent material which acts as an x-ray detector. It stores the x-ray image in the form of excited charge carriers. An exposed imaging plate is loaded into the image reader of the PCR Eleva system and the image stored on the imaging plate is scanned with a laser and converted to digital data. The digital X-ray image data is then routed to the Eleva workstation for image processing, viewing, storing and/or printing to film if the workstations are connected to a compatible laser imager. The Eleva Workspot is also used for the scheduling of patients and exams. The Eleva Workstation consists of a PC, a keyboard, a monitor, and an optional bar-code reader.

The provided document is a 510(k) submission for the Philips PCR Eleva 1.2, a digital film processing system. It outlines the device's identification, predicate device, indications for use, and a summary of nonclinical tests. However, it does not contain the detailed information required to answer all aspects of your request regarding acceptance criteria and a specific study proving the device meets those criteria, particularly within the context of AI performance or clinical efficacy studies.

This submission is a Special 510(k), which focuses on modifications to an existing device (Philips PCR 5.2). The core claim is that these modifications do not change the indications for use or alter the fundamental scientific technology, and therefore, the new device is at least as safe and effective as the predicate. The "study" referenced is primarily a verification and validation process against requirement specifications and risk management results, rather than a clinical trial demonstrating performance against specific clinical metrics.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. Table of acceptance criteria and the reported device performance

The document states: "All acceptance criteria for a product release according to our product release policy are met." However, it does not explicitly list the specific acceptance criteria or provide a table of reported device performance against those criteria. It generally refers to "requirement specifications and risk management results" and "software verification, validation and DICOM conformance testing" as areas where tests were performed.

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 provided in the document. The submission mentions "verification and validation tests were performed on the complete system," but it does not detail the nature of a specific test set (e.g., patient images), its sample size, or its provenance.

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 provided. As the submission primarily concerns system modifications and verification, and not a clinical performance study with human readers assessing images, the concept of "ground truth established by experts" for a test set in the clinical sense is not discussed.

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

This information is not provided.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

There is no mention of an MRMC comparative effectiveness study, nor any discussion of AI assistance or its effect size on human readers. This submission predates widespread integration and evaluation of AI in medical imaging devices in this manner (2009). The device is described as a "digital film processing system," which digitizes X-ray images for viewing, storage, post-processing, and printing. It is not presented as an AI-powered diagnostic aid.

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

This information is not applicable/provided in the context of an AI algorithm. The device itself is a system for processing and managing images, not a standalone diagnostic algorithm.

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

The document does not detail how "ground truth" (in a clinical sense related to disease presence/absence) was established for any specific image test set. The "ground truth" in this context refers to the device's functional performance against its technical specifications and regulatory requirements, not clinical diagnostic accuracy.

8. The sample size for the training set

This information is not provided and is not applicable in the context of this device development, as it is not an AI-driven system that would typically undergo a "training" phase with a dataset of labeled clinical images.

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

This information is not provided and is not applicable for the reasons stated above.

In summary:

The Philips PCR Eleva 1.2 Special 510(k) submission describes updates to a Computed Radiography system. The "study" referred to is a series of nonclinical verification and validation tests (software, DICOM conformance, and assessment against requirement specifications and risk management results) ensuring the modified device remains as safe and effective as its predicate. It does not present clinical performance data, AI performance metrics, or details about expert-adjudicated test sets. The nature of this 510(k) (Special 510(k) for device modifications) means a full-scale clinical trial with specific performance metrics against a defined acceptance criterion and a large, expert-adjudicated test set was likely not deemed necessary by the manufacturer or required by the FDA at the time for this type of device modification.

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Pinnacle Radiation Therapy Planning System is a computer software package intended to provide support for radiation therapy treatment planning for the treatment of benign or malignant disease processes.

Pinnacle Radiation Therapy Planning System assists the clinician in formulating a treatment plan that maximizes the dose to the treatment volume while minimizing the dose to the surrounding normal tissues. The system is capable of operating in both the forward planning and inverse planning modes.

The device is indicated for use in patients deemed to be acceptable candidates for radiation treatment in the judgment of the clinician responsible for patient care.

Plans generated using this system are used in the determination of the course of a patient's radiation treatment. They are to be evaluated, modified and implemented by qualified medical personnel.

SmartArc is a module for creating intensity modulated arc therapy plans.

The SmartArc module is an extension of PIMRT that adds dynamic arc capabilities. A Dynamic Arc beam is similar to the current Conformal Arc bean but does ot impose the restrictions of a constant does rate or blocking a specific target.

The SmartArc solution utilizes continuous gantry motion in which the field shape defined by a multi-leaf collimator changes during gantry rotation. The dose rate can also be changed during rotation of the gantry.

Creation of a Dynamic Arc beam will be accomplished through a SmartArc optimization. The user will create a default Dynamic Arc beam, enter IMRT, assign objectives and perform a SmartArc optimization to provide an intensity Modulated Arc Treatment )IMAT) plan.

This extends the functionality of the Pinnacle3 Radiation Therapy Planning System (hereafter Pinnacle RTP) that provides radiation therapy planning for the treatment of benign or malignant diseases. When using Pinnacle RTP, qualified medical personnel may generate, review, verify, approve, print and export the radiation therapy plan prior to patient treatment. Pinnacle RTP can provide plans for various radiation therapy modalities including External Beam Treatment, Stereotactic Radiosurgery, and Brachytherapy.

Pinnacle RTP is a software package that runs on a Sun UNIX workstation and consists of a core software module (Pinnacle') and optional software features. These optional software features, commonly referred to as "plug-ins", are typically distributed separate from the core software product (separate CD-ROM). The device has network capability to other Pinnacle RTP workstations and to both input and output devices via local area network (LAN) or wide area network (WAN).

This software automates multi-modality image registration and fusion by overlaying images from CT. MR. PET. PET-CT, and SPECT devices. This feature provides clinicians with the ability to relate, interpret and contour and image's anatomic and functional information.

The provided text describes the 510(k) premarket notification for the Philips Medical Systems (Cleveland), Inc. Pinnacle3 Radiation Therapy Planning System SmartArc Module. However, it does not contain explicit acceptance criteria in a quantitative format or a detailed study proving the device meets specific performance criteria as typically found in clinical validation studies.

The document primarily focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against pre-defined acceptance criteria through detailed clinical or non-clinical testing results.

Here's a breakdown of the information that can be extracted, and what is not present:

1. Table of Acceptance Criteria and Reported Device Performance:

This information is not explicitly provided in the document. The submission focuses on demonstrating substantial equivalence, meaning the device performs similarly to existing legally marketed devices, rather than meeting specific numerical performance targets.

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

• Test Set Sample Size: Not specified. The document states a "Summary of Non-Clinical Tests" was completed, but does not detail the size or nature of the test cases used for verification and validation.
• Data Provenance (Country of Origin, Retrospective/Prospective): Not specified.

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

This information is not provided. As clinical testing was not deemed necessary for substantial equivalence, there's no mention of experts or ground truth establishment for a test set in the context of clinical performance.

4. Adjudication Method for the Test Set:

This information is not provided.

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

• Was it done?: No. The document explicitly states: "Summary of Clinical Tests: Clinical testing is not required to demonstrate substantial equivalence or safety and effectiveness." Therefore, an MRMC study comparing human readers with and without AI assistance was not conducted or reported in this submission.
• Effect Size: Not applicable, as no such study was performed.

6. Standalone (Algorithm Only) Performance Study:

• Was it done?: Not explicitly as a separate performance study with reported metrics. The "Summary of Non-Clinical Tests" mentions "Verification and Validation test plans were completed...to demonstrate that the Pinnacle Radiation Therapy Planning System SmartArc has met its specifications, demonstrates substantially equivalent performance to the predicate devices and is safe and effective for its intended use." This suggests internal testing of the algorithm's functionalities and adherence to specifications, but no detailed, standalone performance metrics (e.g., accuracy, precision) are provided for the SmartArc module itself. The focus is on the dose computation algorithms (CCCS, SVD) which are part of the overall system.

7. Type of Ground Truth Used:

This information is not explicitly provided for the "test set" in the context of a performance study. For the internal verification and validation, the ground truth would likely be established by comparing algorithm outputs against known physics models, theoretical calculations, and potentially against predicate device performance.

8. Sample Size for the Training Set:

This information is not provided. As the device uses established dose computation algorithms (CCCS, SVD) and is an extension of existing software, it's unlikely there was a separate "training set" in the machine learning sense that would require a specified sample size. The algorithms themselves are based on physics models rather than deep learning training data.

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

This information is not provided, as the concept of a "training set" with established ground truth in the typical machine learning sense doesn't directly apply here. The dose computation algorithms described (CCCS, SVD) are physics-based models, and their "ground truth" comes from fundamental physics principles, Monte Carlo simulations, and established mathematical formulations (as indicated by the references to Mackie et al. and Bortfeld).

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The HeartStart 12 Lead Transfer Station SW provides a diagnostic 12 lead ECG interface between Philips defibrillators and ECG management systems that can process XML formatted ECGs, such as the TraceMasterVue ECG Management system.

The HeartStart 12 Lead Transfer Station also allows viewing, printing, archiving and further distribution of digitized ECG records.

The 12 Lead Transfer Station facilitates transmission of diagnostic 12 Lead ECG reports from Philips Defibrillators to ECG Management systems that recognize and accept digitized ECG records using the Philips published ECG schema. The Philips TraceMasterVue ECG System is a computer system which allows viewing, manual editing, printing, and archiving of digitized ECG records. TraceMasterVue communicates with Web-based clients, faxes, printers etc through an industry-standard client/server network with other hospital information systems.

The provided text does not contain detailed information about specific acceptance criteria or a comprehensive study report with the requested metrics. The document is a 510(k) summary and an FDA clearance letter for the Philips HeartStart 12 Lead Transfer Station. It broadly states that "Verification, validation, and testing activities establish the performance and functionality characteristics of the new device" and "test results showed substantial equivalence."

Therefore, I cannot provide a table of acceptance criteria and reported device performance or elaborate on the specific study details (sample size, data provenance, expert involvement, adjudication, MRMC studies, standalone performance, ground truth types, or training set information) because these details are not present in the provided text.

The document primarily focuses on:

• Device Identification: Name, classification, and contact information.
• Intended Use: Facilitates transmission of diagnostic 12 Lead ECG reports from Philips Defibrillators to ECG Management systems.
• Substantial Equivalence: Declares the new device is substantially equivalent to the previously cleared M5100A TraceMasterVue ECG Management System (K032103).
• Testing Approach (High-Level): Mentions system-level tests, integration tests, and regression tests from hazard analysis.
• Conclusion: States that "Pass/Fail criteria were based on the specifications and test results showed substantial equivalence. The results demonstrate that the functionality of the modified ECG Management System meets all performance claims."

To obtain the detailed information requested, one would typically need to consult the complete 510(k) submission, including the detailed V&V reports, which are not publicly available in this summary format.

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The Philips reusable and disposable SpO2 Sensors are intended for non-invasive measurement of oxygen saturation (SpO2) and pulse rate.

Philips Reusable SpO2 Sensors M1191T, M1192T, and M1193T: M1191T is indicated for adult patients, M1192T is indicated for pediatric patients, and M1193T is indicated for neonatal patients.

Philips SpO2 Reusable Clip Sensor Model M1196T: M1196A and M1196T are indicated for patients > 40 kg (typically adult patients).

Philips Disposable SpO2 Sensor M1131A: M1131A is indicated for adult patients/pediatric patients

Philips Disposable SpO2 Sensors M1132A and M1133A: M1132A is indicated for infant patients, and M1133A for adult/infant/neonatal patients.

Not Found

The provided text discusses regulatory approval for Philips SpO2 sensors but does not contain information about acceptance criteria or a study proving device performance against specific criteria. The document describes a 510(k) submission for a labeling change to add compatibility with non-Philips monitors. The testing mentioned in the document states "Verification, validation, and testing activities establish the performance, functionality, and reliability characteristics of the new device with respect to the predicate. Testing involved system level tests, integration tests, environmental tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate device and test results showed substantial equivalence. The results demonstrate that the pulse oximetry sensors functionality meets all reliability requirements and performance claims." However, it does not provide details on specific acceptance criteria values, reported device performance metrics, sample sizes, data provenance, ground truth establishment, or any comparative effectiveness studies.

Therefore, I cannot populate the table or answer the specific questions about acceptance criteria and study details based on the provided text.

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M3290A: For central monitoring of multiple adult, pediatric, and neonatal patients; and where the clinician decides to monitor cardiac arrhythmia of adult, pediatric, and neonatal patients and/or ST segment of adult patients to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

M4840A: For ambulatory and bedside monitoring of ECG and SpO2 parameters of adult and pediatric patients in healthcare facilities to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

The Philips M3290A IntelliVue Information Center Software Release F.0 and M4840A Philips Telemetry System II with M4841A patient device.

This Philips submission for the M3290A IntelliVue Information Center Software Release F.0 and M4840A Philips Telemetry System II with M4841A patient device describes modifications (changes in ECG chest lead support, NBP limit alarms, and network functionality) and asserts substantial equivalence to a previously cleared predicate device (K040357). The documentation does not contain a detailed study with specific acceptance criteria and device performance metrics, as would typically be presented for de novo device approval or significant design changes requiring new clinical validation.

Instead, the submission states that:

"Verification, validation, and testing activities have successfully established the performance, functionality, and reliability characteristics of the new devices with respect to the predicates. Testing involved system level tests, integration tests, environmental tests, and safety testing from hazard analysis. Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results showed substantial equivalence. The results successfully demonstrate that patient monitoring system functionality meets all reliability requirements and performance claims and is substantially equivalent to the predicate devices."

This indicates that the modifications were evaluated against the established performance specifications of the predicate device, and the testing confirmed that the changes did not degrade performance below those existing benchmarks.

Therefore, not all questions can be directly answered as the provided text does not contain a discrete study with defined acceptance criteria and performance data for this specific submission's modifications. The information below reflects what can be extracted or inferred from the provided text regarding the evaluation approach.

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, specific quantitative acceptance criteria and detailed device performance metrics (true positive rate, false positive rate, sensitivity, specificity, accuracy, AUC, F1-score) are not explicitly stated for the modified device. The document states that "Pass/Fail criteria were based on the specifications cleared for the predicate devices and test results showed substantial equivalence." This implies that the device maintained the performance characteristics of its predicate.

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

• Test set sample size: Not specified. The testing described includes "system level tests, integration tests, environmental tests, and safety testing from hazard analysis," which are typically internal engineering and validation tests rather than clinical studies with patient data in the context of AI/ML evaluation.
• Data provenance: Not specified. Given the nature of the modifications (adding support for an ECG chest lead, NBP alarms, network functionality), the testing likely involved controlled testing environments and simulated data, potentially with some real physiological data from internal archives if applicable, but no geographically or retrospectively/prospectively defined clinical dataset is mentioned.

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

• Not applicable/Not specified. The evaluation focused on technical performance and substantial equivalence to a predicate device, not on diagnostic accuracy requiring expert ground truth labels for a dataset.

4. Adjudication method for the test set

• Not applicable/Not specified. There is no mention of a human adjudication process for establishing ground truth for a test set.

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 was performed or mentioned. This submission does not describe an AI/ML algorithm intended to assist human readers.

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

• The device itself is a patient monitoring system, which includes automated capabilities like arrhythmia detection and ST segment monitoring. The testing described implicitly evaluates these "standalone" functionalities against their specifications, as part of assessing substantial equivalence to the predicate. However, specific performance metrics for individual algorithms (e.g., arrhythmia detection algorithm sensitivity) are not provided in this summary.

7. The type of ground truth used

• For the technical and safety testing conducted, the ground truth would be based on device specifications, engineering requirements, and regulatory standards. For example, in testing NBP alarms, the ground truth would be the defined NBP limits and whether the system correctly triggered an alarm when those limits were exceeded based on simulated or measured blood pressure values. For ECG lead support, the ground truth would be the accurate acquisition and display of the ECG signal via the new lead.

8. The sample size for the training set

• Not applicable. This device, as described in this 2004 submission, is a traditional medical device (patient monitor) with pre-specified algorithms, not a machine learning or AI device that undergoes a training phase with a distinct training set.

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

• Not applicable. As noted above, this is not an AI/ML device that requires a training set and associated ground truth establishment.

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Indicated for central monitoring of multiple adult, pediatric, and neonatal patients; and where the clinician decides to monitor cardiac arrhythmia of adult, pediatric, and neonatal patients and/or ST segment of adult patients to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

M3290A IntelliVue Information Center Software Release E.01 and IntelliVue Clinical Network on VLAN. The modification is a change that permits operation of the IntelliVue Clinical Network on customer provided IEEE 802.1q compatible VLAN network infrastructure.

This 510(k) pertains to a software update (Release E.01) for the M3290A IntelliVue Information Center and its operation on a VLAN. The submission focuses on demonstrating substantial equivalence to previously cleared versions of the device, rather than presenting a de novo study with acceptance criteria and performance metrics for a new medical device. The document primarily highlights that the updated device maintains the same performance, functionality, and reliability characteristics as its predicate devices.

Therefore, much of the requested information regarding detailed acceptance criteria, specific performance metrics, sample sizes for test/training sets, ground truth establishment, and expert involvement for a new device's performance evaluation is not explicitly provided in this 510(k) summary. The document emphasizes verification, validation, and testing activities to ensure the updated software and network capabilities meet established specifications for the predicate device.

However, based on the provided text, here's what can be extracted and inferred:

1. A table of Acceptance Criteria and the Reported Device Performance:

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 for Test Set: Not specified. The document states "Testing involved system level tests, integration tests, environmental tests, and safety testing from hazard analysis." This suggests a battery of tests rather than a single, defined patient-data test set.
• Data Provenance: Not specified. Given the nature of the update (software and network compatibility), the testing might have been primarily internal engineering and software validation, rather than extensive clinical data.

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

• Not specified. The ground truth for this type of software and network update would likely be based on technical specifications and expected system behavior, rather than expert clinical consensus on patient data.

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

• Not specified. Adjudication methods are typically used for clinical endpoints where there's variability in interpretation among experts, which is not directly applicable to a software and network compatibility update.

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. This is a software and network compatibility update for a physiological monitor, not an AI-assisted diagnostic tool.

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

• The testing described ("system level tests, integration tests, environmental tests, and safety testing") would inherently involve evaluation of the algorithm and system performance in a standalone manner (without specific human-in-the-loop clinical performance evaluation as might be done for diagnostic AI). However, this isn't a standalone AI performance study.

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

• For this type of device update, the "ground truth" would be the successful adherence to pre-defined technical specifications, functional requirements, and reliability standards of the predicate device, as well as successful operation within the new VLAN environment. This is an engineering and software validation ground truth, not a clinical diagnostic ground truth.

8. The sample size for the training set:

• Not applicable. This is not a machine learning or AI device that requires a training set in the conventional sense. The "training" would be the development and refinement of the software, and the "test" would be the verification/validation.

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

• Not applicable, as no training set for machine learning was used.

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The Cadex Battery Charger for Philips HeartStart Batteries is used to recharge and analyze rechargeable batteries that are used with Philips HeartStart manual defibrillator/monitors.

The Cadex Battery Charger for Philips HeartStart Batteries is used to charge and analyze rechargeable batteries used in Philips HeartStart defibrillators. The Battery Charger consists of a commercially available battery charger and an adapter specifically designed to interface with the Philips HeartStart batteries. The battery charger is available in 2- and 4-bay models, which allow for the simultaneous charging of up to 4 batteries. The adapters allow for the mechanical interface between the battery and the battery charger. The adapters also contain the software that allows the battery charger to charge the battery using the appropriate algorithm for the type of battery being charged. The battery charger also analyzes a battery to determine its capacity.

The provided text describes the Cadex Battery Charger for Philips HeartStart Batteries and its 510(k) summary, but it does not contain information about specific acceptance criteria or a study proving that the device meets those criteria with numerical performance data.

The document states:

• "Tests Used in Determination of Substantial Equivalence: The tests used in the determination of substantial equivalence included only bench testing. Bench testing includes hardware and software testing demonstrating that the performance of the device meets its specification."

This indicates that internal specifications were used, but the document does not detail those specifications as explicit acceptance criteria or provide the results of the bench testing in terms of reported device performance.

Therefore, I cannot populate the table or answer most of the questions as the specific details of the acceptance criteria, reported performance, and study methodology are not present in the provided text.

Here's a breakdown of what can be inferred from the provided text, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

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 (Test Set): Not specified. The document only mentions "bench testing."
• Data Provenance: Not specified.
• Retrospective/Prospective: Not specified.

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. Bench testing of a battery charger typically relies on engineering specifications and measurement equipment for "ground truth," not human experts in the way clinical studies do.

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

• Not applicable. See point 3.

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 battery charger, not an AI diagnostic device. No MRMC study was conducted.

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

• Not applicable/Not precisely. The "algorithm" here refers to the battery charging and analysis software. The document states "software testing demonstrating that the performance of the device meets its specification," implying standalone testing of the charging functions. However, it's not an "AI algorithm" in the typical sense.

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

• For bench testing of a battery charger, the "ground truth" would typically be established by:
  • Engineering specifications/Design requirements for charging parameters (voltage, current, time).
  • Reference measurement equipment (e.g., calibrated multimeters, power analyzers) for verifying output and charging characteristics.
  • Known battery specifications for capacity and performance.

8. The sample size for the training set

• Not applicable. This is not a machine learning/AI device requiring a training set.

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

• Not applicable. This is not a machine learning/AI device requiring a training set.

Conclusion:

The provided 510(k) summary for the Cadex Battery Charger for Philips HeartStart Batteries indicates that "bench testing" was performed to ensure the device "meets its specification." However, it does not provide the specific acceptance criteria (specifications), the quantitative results of these tests, or detailed methodology regarding sample sizes or the establishment of "ground truth" beyond general engineering principles. No clinical studies, expert reviews, or AI-specific evaluations were part of this submission, which is appropriate for a device of this nature.

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M3290A: For central monitoring of multiple adult, pediatric, and neonatal patients; and where the clinician decides to monitor cardiac arrhythmia of adult, pediatric, and neonatal patients and/or ST segment of adult patients to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

M4840A: For ambulatory and bedside monitoring of ECG and SpO2 parameters of adult and pediatric patients in healthcare facilities to gain information for treatment, to monitor adequacy of treatment, or to exclude causes of symptoms.

The M3290A IntelliVue Information Center Software Release F.0 and M4840A Telemetry System II with M4841A TelePac+. The modification is a change that modifies the ECG processing, adds 4 high priority SpO2 limit alarm conditions and waveform export, and changes the radio technology.

The provided text is a 510(k) summary for the Philips IntelliVue Information Center Software Release F.0 and M4840A Telemetry System II with M4841A TelePac+. While it outlines the device's substantial equivalence to predicate devices and its indications for use, it does not include detailed information regarding specific acceptance criteria, a dedicated study proving device performance against those criteria, or the methodology for establishing ground truth as requested in your prompt.

The document states: "Verification, validation, and testing activities have successfully established the performance, functionality, and reliability established the performance, and many and the predicates. Charactercriberob testing involved by bean environmental ceseb, and based on the specifications cleared for the Pass/rail Criteria Were Dabstantial equivalential equivalence." This is a general statement and does not provide the specifics you're looking for.

Therefore,Based on the provided text, I cannot extract the detailed information requested in your prompt regarding acceptance criteria and the study proving the device meets those criteria. The 510(k) summary focuses on substantial equivalence to predicate devices and general statements about verification and validation, rather than a specific performance study with detailed methodology and results.

Here's a breakdown of what cannot be found in the provided text:

1. Table of Acceptance Criteria and Reported Device Performance: This information is not present. The document mentions "Pass/fail Criteria Were Dabstantial equivalential equivalence" but does not define these criteria or report the device's performance against them.
2. Sample Size Used for the Test Set and Data Provenance: Not mentioned.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications: Not mentioned.
4. Adjudication Method: Not mentioned.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study: Not mentioned. The document primarily discusses the device itself, not its impact on human reader performance.
6. Standalone (Algorithm Only) Performance Study: Not mentioned. The focus is on the device as a whole system.
7. Type of Ground Truth Used: Not mentioned.
8. Sample Size for the Training Set: Not mentioned. (It's worth noting that for a 510(k) in 2004, a "training set" in the modern AI sense might not have been a primary focus or explicitly documented in this manner for a re-submission involving software updates.)
9. How Ground Truth for the Training Set Was Established: Not mentioned.

Conclusion based on the provided text:

The provided document is a 510(k) summary from 2004, which typically focuses on demonstrating substantial equivalence to legally marketed predicate devices rather than providing a detailed performance study with explicit acceptance criteria and corresponding results in the format you've requested. It indicates that the device has undergone verification, validation, and testing to establish its performance, functionality, and reliability, but it does not present the specifics of these tests or their outcomes as a dedicated performance study.

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The Philips Reusable SpO2 Sensors are intended for acquiring non-invasively the arterial oxygen saturation to support the measurement of oxygen saturation.

M1191T is indicated for adult patients, M1192T is indicated for pediatric patients, and M1193T is indicated for neonatal patients.

The Philips SpO2 devices measure, non-invasively, the arterial oxygen saturation of blood. The measurement method is based on the red and infrared light absorption of hemoglobin and oxyhemoglobin. Light of a red and infrared light source is emitted through human tissue and received by a photodiode.

The measurement is based on the absorption of light, which is emitted through human tissue (for example through the index finger). The light comes from two sources (red LED and infrared LED) with different wavelengths and is received by a photodiode. Out of the different absorption behavior of the red and infrared light a so-called Ratio can be calculated. The saturation value is defined by the percentage ratio of the oxygenated hemoglobin [HbO2] to the total amount of hemoglobin [Hb].

SpO2 = [HbO2]/([Hb]+[HbO2])

Out of calibration curves, which are based on controlled hypoxia studies with healthy non-smoking adult volunteers over a specified saturation range (SaO2 from 100%-70%), the Ratio can be related to a SpO2 value.

The devices contain a red and infrared light source and a photodiode receiving the non-absorbed red and infrared light. The received signals are forwarded to a measurement device that amplifies the acquired signal and an algorithm that calculates the ratio and converts via a validated calibration table the ratio to a saturation value.

The provided text describes a 510(k) submission for Philips Reusable SpO2 Sensors. Here's a breakdown of the requested information:

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

The document does not explicitly state quantitative acceptance criteria in a dedicated table format. However, it indicates that "clinical evaluations for accuracy" were conducted and "Test results showed substantial equivalence." The basis for calibrating the saturation values is described: "Out of calibration curves, which are based on controlled hypoxia studies with healthy non-smoking adult volunteers over a specified saturation range (SaO2 from 100%-70%), the Ratio can be related to a SpO2 value."

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 mentions "controlled hypoxia studies with healthy non-smoking adult volunteers."

• Sample Size: Not explicitly stated, but implies a cohort of "healthy non-smoking adult volunteers."
• Data Provenance: The study involved human volunteers, making it a prospective clinical study. The location of the study is not specified, but the applicant (Philips Medizin Systeme Boeblingen GmbH) is based in Germany, and typically such studies would be conducted in the country of origin or a relevant regulatory jurisdiction.

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)

The establishment of ground truth ("calibration curves") for SpO2 measurements in hypoxia studies typically involves:

• Ground Truth Method: Direct arterial blood gas analysis, which is considered the gold standard for arterial oxygen saturation (SaO2).
• Number of Experts/Qualifications: The document does not specify the number or qualifications of medical professionals (e.g., intensivists, pulmonologists, clinical researchers) involved in conducting the hypoxia studies or performing arterial blood gas measurements. However, such studies are inherently under the supervision of qualified medical personnel.

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

The document does not describe an adjudication method as it pertains to expert consensus on interpretation. For SpO2 measurement, the ground truth (direct SaO2 from blood gas) is a quantitative measurement, not subject to subjective adjudication by multiple readers in the same way an image interpretation might be.

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. This device is a sensor (hardware) that provides a direct physiological measurement (SpO2), not an AI-driven interpretation system that assists human readers.

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

• Yes, a form of standalone performance was assessed. The device itself, as an oximeter sensor and an internal algorithm, calculates the SpO2 value. The "clinical evaluations for accuracy" and "calibration curves" against directly measured SaO2 from blood gases represent a standalone performance assessment of the device's ability to accurately measure SpO2. This is the device operating without human judgment to interpret the output.

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

The ground truth used for establishing the calibration curves was physiologically derived actual arterial oxygen saturation (SaO2), typically measured via co-oximetry from arterial blood samples. This is obtained during "controlled hypoxia studies."

8. The sample size for the training set

The document refers to "controlled hypoxia studies with healthy non-smoking adult volunteers" for establishing calibration curves. The sample size for these calibration studies is not explicitly stated.

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

The ground truth for the calibration curves (which serve as the basis for the device's "training" or fundamental operational logic) was established through controlled hypoxia studies. In these studies, healthy volunteers' arterial oxygen saturation (SaO2) was varied and simultaneously measured using a gold standard method (e.g., co-oximetry via arterial blood gas analysis) while the device's raw signal ratio was recorded. This allowed for the correlation of the device's internal ratio to a true SaO2 value, creating the "validated calibration table."

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Indicated for use by health care professionals whenever there is a need for monitoring the physiological parameters of patients. Intended for monitoring, recording and alarming of multiple physiological parameters of adults, pediatrics and neonates in patient transport and hospital environments.

picoSAT II SpO2 pulse oximetry module and M3001A Multi-Measurement Server

The provided text is a 510(k) summary for the picoSAT II SpO2 pulse oximetry module. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does NOT contain the detailed information required to fill out the table regarding acceptance criteria and the specific study proving the device meets those criteria.

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

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

• Acceptance Criteria: Not explicitly stated in the provided text. Pulse oximeter performance is typically measured by accuracy (Arms) over a specified SpO2 range.
• Reported Device Performance: Not explicitly stated. The document mentions "clinical validation studies were also conducted" but does not provide the results of these studies or any performance metrics.

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 (Test Set): Not mentioned.
• Data Provenance: Not mentioned.

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)

• Number of Experts: Not applicable, as this is a pulse oximetry device, not an image-based diagnosis device usually requiring expert interpretation for ground truth. The "ground truth" for a pulse oximeter would likely be arterial blood gas measurements (co-oximetry).
• Qualifications of Experts: Not applicable.

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

• Adjudication Method: Not applicable for a pulse oximetry device where direct physiological measurements usually serve as the reference.

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

• MRMC Study: Not applicable. This is not an AI-assisted diagnostic device for human readers.

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

• Standalone Performance: The core of a pulse oximeter is a standalone algorithm. The document mentions "clinical validation studies were also conducted," which would imply testing the device's accuracy in measuring SpO2. However, no specific performance results (like Arms) are provided.

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

• Type of Ground Truth: Not explicitly stated, but for pulse oximeters, the gold standard for ground truth is typically arterial blood gas analysis (co-oximetry).

8. The sample size for the training set

• Sample Size (Training Set): Not mentioned. "Training set" is generally more relevant for machine learning algorithms. While the device uses a "FAST pulse oximetry algorithm," the document doesn't detail how this algorithm was developed or if it involved a distinct "training set" in the modern machine learning sense. Clinical validation would be a more direct performance test.

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

• Ground Truth (Training Set): Not mentioned.

Summary of what is present and what is missing:

The provided text serves as a 510(k) summary, which generally focuses on demonstrating substantial equivalence to predicate devices and adherence to regulatory requirements. It confirms that "clinical validation studies were also conducted" and "all verification and validation activities were successfully completed," but it explicitly lacks the detailed results, acceptance criteria, sample sizes, and ground truth methodologies that would typically be found in a detailed study report or a more comprehensive technical document.

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