Radiological Machine Learning Based Quantitative Imaging Software With Change Control Plan
The Radiological Machine Learning Based Quantitative Imaging Software with Change Control Plan is a software-only medical device that employs machine learning algorithms on radiological images to generate quantitative imaging outputs, including view selection, segmentation, and landmarking functions, and is designed with a predetermined change control plan that permits specified modifications to the device's machine learning algorithms over time without requiring a new premarket submission for each update. Classified as FDA Class 2 under regulation 892.2055, it requires 510(k) clearance in the Radiology specialty. The device is not an implant and not life-sustaining.
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Basic Information
- Product Code
- QVD
- Device Class
- FDA class 2
- Regulation Number
- 892.2055
- Medical Specialty
- Radiology
- Review Panel
- RA
- Submission Type
- 1
Device Characteristics
Definition
A radiological machine learning quantitative imaging software with predetermined change control plan is a software-only device which employs machine learning algorithms on radiological images to provide quantitative imaging outputs. The device includes functions to support outputs such as view selection, segmentation and landmarking. The design specifications include planned modifications that may be made to the device consistent with an established predetermined change control plan.
510(k) Clearance History
Related 510(k) Clearances
This FDA classification is associated with 1 510(k) clearance via K numbers.
| K Number | Device Name | Decision Date | Decision | Applicant |
|---|---|---|---|---|
| DEN220063 | Caption Interpretation Automated Ejection Fraction Software | Feb 24, 2023 | Unknown | Caption Health, Inc. |
FEI Numbers
This FDA classification entry is associated with 1 FEI number. Click on an entry to view related FDA registrations.
Registration Numbers
This FDA classification entry is associated with 1 registration number. Click on an entry to view related FDA registrations.