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510(k) Data Aggregation
(247 days)
The indications for use statement for the proposed Interventional Workspot software medical device, as presented in the IFU, are as follows:
The Interventional Workspot has the following medical purpose:
- import, export, and store digital clinical images.
- manage the patient information associated with those images.
The Interventional Workspot software medical device is a software platform for hosting the aforementioned currently marketed and predicate software medical devices. It provides the same functionalities (for example, import, export, and data handling) that are required by the aforementioned currently marketed and predicate software medical devices to support the physician with performing interventional procedures.
The interventional workspot is a software platform to host Interventional Tools. It provides common functionalities (e.g. import / export and data handling functions) that are required by the Interventional Tools to support the physician with performing the interventional procedure.
This 510(k) summary describes Philips Interventional Workspot, a software platform intended to host other interventional tools, providing functionalities such as import, export, and data handling of digital clinical images and patient information.
Here's an analysis of the provided information regarding acceptance criteria and the study that proves the device meets them:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly state quantitative acceptance criteria or detailed performance metrics. It indicates that the device underwent non-clinical verification and validation tests.
Acceptance Criteria Category | Reported Device Performance |
---|---|
Functional Verification | Interventional Workspot met the acceptance criteria. |
Validation | Interventional Workspot met the acceptance criteria. |
DICOM Conformance | Interventional Workspot met the acceptance criteria. |
Compliance with Standards | Complies with international recognized standards. |
Risk Management Results | Performed as part of non-clinical verification and validation tests. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify a "test set" in the context of clinical data or patient samples. The testing described is "non-clinical verification and validation tests," implying software-based evaluations rather than studies involving patient data. Therefore, details regarding test set sample size and data provenance (country of origin, retrospective/prospective) are not provided and do not appear to be relevant to the type of testing performed for this device.
3. Number of Experts Used to Establish Ground Truth and Qualifications
Not applicable. As the testing was non-clinical verification and validation of software functionalities, there was no "ground truth" related to medical diagnoses or human interpretation that would require expert adjudication.
4. Adjudication Method
Not applicable. No expert adjudication process is described for non-clinical software testing.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No. The document does not describe a multi-reader, multi-case comparative effectiveness study involving human readers or the effect size of AI assistance. This device is a software platform, not an AI-powered diagnostic tool, so such a study would not typically be conducted.
6. Standalone (Algorithm Only) Performance Study
Yes, in the sense that the "Summary of testing" details non-clinical verification and validation tests indicating the algorithm/software's standalone performance in meeting its functional requirements and regulatory standards. However, it's not a standalone clinical performance study as might be conducted for a diagnostic algorithm. The statement "The results of these tests demonstrate that Interventional Workspot met the acceptance criteria" refers to the software's performance in isolation from clinical application.
7. Type of Ground Truth Used
The "ground truth" for the non-clinical verification and validation tests would be the pre-defined requirement specifications and expected behavior of the software functionalities (e.g., successful import/export, correct data handling, DICOM compliance). It does not involve expert consensus, pathology, or outcomes data, as these are related to clinical efficacy or diagnostic accuracy, which are not the focus of this device's testing.
8. Sample Size for the Training Set
Not applicable. This device is described as a software platform providing functionalities like import, export, and data handling. It is not an AI/ML algorithm that requires a "training set" of data in the conventional sense to learn patterns or make predictions. Its development would involve software engineering and testing against functional specifications.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there is no "training set" for this type of software platform. The "ground truth" for its development and testing would be derived from its design specifications and compliance with relevant industry standards (e.g., DICOM for image handling).
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