AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K243681 · Jul 23, 2025
Neuro Insight V1.0
Olea Medical S.A.S.
Retrospective clinical MR imaging datasets from multiple manufacturers
Retrospective clinical MR volumes were used to train and validate a 3D U-Net deep learning algorithm for brain extraction (BET).
Deep learning; Brain extraction; Retrospective clinical data; Algorithm training
Clinical Evidence
Study Design
Population
Comparator
Key Endpoints
Deep learning algorithm training and validation dataset; Retrospective analysis of clinical MR volumes
Diverse patient population (mean age 60, range 14-100) across multiple MRI manufacturers (GE, Siemens, Philips, Canon); Sample Size: 362 MR volumes; Number of Sites: Multiple (implied by multi-manufacturer source)
Not applicable for this study
DICE coefficient (average 0.97) and Tversky metrics for brain extraction accuracy
All 6 co-registrations considered acceptable for reading and interpretation
—
—
60 anonymized brain MRI cases
3 (US neuroradiologists)
Indications for Use
Neuro Insight V1.0 is an image processing solution. It is intended to assist appropriately trained medical professionals in their analysis workflow on neurological MRI images. Neuro Insight V1.0 is composed of two subsets, including an image processing application package (NeuroPro) and an optional user interface (Neuro Synchronizer). NeuroPro is an image processing application package that computes maps, extracts and communicates metrics which are to be used in the analysis of multiphase or monophase neurological MR images. NeuroPro can be integrated and deployed through technical integration environment, responsible for transferring, storing, converting formats and displaying of DICOM imaging data. Neuro Synchronizer is an optional dedicated interface allowing the viewing, manipulation, and comparison of neurological medical imaging and/or multiple time-points, including post-processing results provided by NeuroPro or any other results from compatible processing applications. Neuro Synchronizer is a medical image management application intended to enable the user to edit and modify parameters that are optional inputs of aforementioned applications. These modified parameters are provided through the technical integration environment as inputs to the application to reprocess outputs. If necessary, Neuro Synchronizer provides the user with the option to validate the information. Neuro Synchronizer can be integrated in compatible technical integration environments. The device does not alter the original medical image. Neuro Insight V1.0 is not intended to be used as a standalone diagnostic device and should not be used as the sole basis for patient management decisions. The results of Neuro Insight V1.0 are intended to be used in conjunction with other patient information and based on professional judgment to assist with reading and interpretation of medical images. Users are responsible for viewing full images per the standard of care.
Device Story
Neuro Insight V1.0 is a neurological MRI image processing solution comprising two subsets: NeuroPro (processing application) and Neuro Synchronizer (optional visualization/manipulation interface). It accepts DICOM neurological MR images (FLAIR, T1, T2, T1g, diffusion, DSC perfusion) as input. NeuroPro computes parametric maps (CBV, CBF, MTT, TTP, Tmax/Delay, CBV_corr, K2, tMIP) and extracts metrics. Neuro Synchronizer allows users to view, compare, and edit optional input parameters (e.g., arterial input function) for reprocessing. Used in clinical/hospital environments by trained professionals; output assists in reading/interpretation of images. Does not alter original images. Benefits include automated, reproducible neuroimaging analysis to support clinical decision-making.
Clinical Evidence
Bench testing only. Performance validated using 30 anonymized brain MRI cases for parametric map computation and 60 cases for co-registration, evaluated by three US board-certified neuroradiologists. Results confirmed substantial equivalence to predicate. Brain extraction algorithm (3D U-Net) validated on 362 volumes (199 train, 63 validation, 100 test) achieving average DICE coefficient of 0.97 (range 0.907-0.988).
Technological Characteristics
Software-based image processing system. Processes FLAIR, T1, T2, T1g, diffusion, and DSC perfusion MRI. Features 3D rigid motion correction, 3D U-Net deep learning brain extraction, and 3D rigid 6-dof co-registration. Connectivity via DICOM integration. Operates on standard clinical hardware environments.
Indications for Use
Indicated for appropriately trained medical professionals to assist in the analysis workflow of neurological MRI images (multiphase or monophase). Not for standalone diagnosis; not for sole basis of patient management decisions.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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FDA U.S. FOOD & DRUG ADMINISTRATION
July 23, 2025
Olea Medical S.A.S.
% John J. Smith
Partner
Hogan Lovells US LLP
Columbia Square 555 Thirteenth Street, NW
Washington, District of Columbia 20004
Re: K243681
Trade/Device Name: Neuro Insight V1.0
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: LLZ
Dated: July 7, 2025
Received: July 7, 2025
Dear John J. Smith:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K243681 - John J. Smith
Page 2
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reporting-combination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
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K243681 - John J. Smith
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For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
Ningzhi
Li-S
Digitally signed by
Ningzhi Li-S
for
Daniel M. Krainak, Ph.D.
Assistant Director
Magnetic Resonance and Nuclear Medicine Team
DHT8C: Division of Radiological Imaging and Radiation Therapy Devices
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120
Expiration Date: 07/31/2026
See PRA Statement below
Submission Number (if known)
K243681
Device Name
Neuro Insight V1.0
Indications for Use (Describe)
Neuro Insight V1.0 is an image processing solution. It is intended to assist appropriately trained medical professionals in their analysis workflow on neurological MRI images.
Neuro Insight V1.0 is composed of two subsets, including an image processing application package (NeuroPro) and an optional user interface (Neuro Synchronizer).
NeuroPro is an image processing application package that computes maps, extracts and communicates metrics which are to be used in the analysis of multiphase or monophase neurological MR images.
NeuroPro can be integrated and deployed through technical integration environment, responsible for transferring, storing, converting formats and displaying of DICOM imaging data.
Neuro Synchronizer is an optional dedicated interface allowing the viewing, manipulation, and comparison of neurological medical imaging and/or multiple time-points, including post-processing results provided by NeuroPro or any other results from compatible processing applications.
Neuro Synchronizer is a medical image management application intended to enable the user to edit and modify parameters that are optional inputs of aforementioned applications. These modified parameters are provided through the technical integration environment as inputs to the application to reprocess outputs. If necessary, Neuro Synchronizer provides the user with the option to validate the information.
Neuro Synchronizer can be integrated in compatible technical integration environments.
The device does not alter the original medical image. Neuro Insight V1.0 is not intended to be used as a standalone diagnostic device and should not be used as the sole basis for patient management decisions. The results of Neuro Insight V1.0 are intended to be used in conjunction with other patient information and based on professional judgment to assist with reading and interpretation of medical images. Users are responsible for viewing full images per the standard of care.
Type of Use (Select one or both, as applicable)
☑ Prescription Use (Part 21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)
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510(K) SUMMARY
Olea Medical's Neuro Insight V1.0
(K243681)
Submitter
Olea Medical
93 avenue des Sorbiers, ZI ATHELIA IV
13600, La Ciotat
France
Phone: +33 4 42 71 24 20
Facsimile: +33 4 42 71 24 27
Contact Person: Nathalie Palumbo
Date Prepared: July 22, 2025
Device Identification
Name of Device: Neuro Insight V1.0
Common Name: Medical image management and processing system
Classification Name: System, Image Processing, Radiological
Regulation No: 892.2050
Product Code: LLZ
Legally Marketed Predicate Device
510(k): K152602
Trade Name: Olea Sphere V3.0
Manufacturer: Olea Medical
Product Code: LLZ
Legally Marketed Reference Devices
510(k): K223502
Trade Name: MR Diffusion Perfusion Mismatch V1.0
Manufacturer: Olea Medical
Product Code: LLZ
510(k): K223532
Trade Name: Olea S.I.A Neurovascular V1.0
Manufacturer: Olea Medical
Product Code: LLZ
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# Device Description Summary
Neuro Insight (NEU_INS_MM) V1.0 product is a neurological image analysis solution, composed of several image processing applications and optional visualization and manipulation features.
Neuro Insight V1.0 is composed of two subsets:
- NeuroPro (NEU_PRO_MR) as an image application package, responsible for the processing of specific neurological MR Images.
- Neuro Synchronizer (NEU_HMI_MM) as an optional image analysis environment, that provides the user interface which has visualization and manipulation tools and allows the user to edit the parameters of compatible applications.
Neuro Insight does not alter the original medical image and is not intended to be used as a diagnostic device.
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# Intended Use / Indications for Use
Neuro Insight V1.0 is an image processing solution. It is intended to assist appropriately trained medical professionals in their analysis workflow on neurological MRI images.
Neuro Insight V1.0 is composed of two subsets, including an image processing application package (NeuroPro) and an optional user interface (Neuro Synchronizer).
NeuroPro is an image processing application package that computes maps, extracts and communicates metrics which are to be used in the analysis of multiphase or monophase neurological MR images.
NeuroPro can be integrated and deployed through technical integration environment, responsible for transferring, storing, converting formats and displaying of DICOM imaging data.
Neuro Synchronizer is an optional dedicated interface allowing the viewing, manipulation, and comparison of neurological medical imaging and/or multiple time-points, including post-processing results provided by NeuroPro or any other results from compatible processing applications.
Neuro Synchronizer is a medical image management application intended to enable the user to edit and modify parameters that are optional inputs of aforementioned applications. These modified parameters are provided through the technical integration environment as inputs to the application to reprocess outputs. If necessary, Neuro Synchronizer provides the user with the option to validate the information.
Neuro Synchronizer can be integrated in compatible technical integration environments.
The device does not alter the original medical image. Neuro Insight V1.0 is not intended to be used as a standalone diagnostic device and should not be used as the sole basis for patient management decisions. The results of Neuro Insight V1.0 are intended to be used in conjunction with other patient information and based on professional judgment to assist with reading and interpretation of medical images. Users are responsible for viewing full images per the standard of care.
# Indications for Use Comparison
Both Neuro Insight V1.0 and Olea Sphere® V3.0 are user-defined software analysis tools used for the analysis of magnetic resonance imaging (MRI) studies. Both devices are intended for use in Clinical/Hospital Environment, by any trained professional. Importantly, neither software product is used for diagnosis. Patient management decisions should not be based solely on the results of either software.
The minor difference in the indications for use between the two devices is that Neuro Insight V1.0 subject device provides processing capabilities for MR only whereas Olea Sphere® V3.0 predicate device provides processing capabilities for both MR and CT.
Neuro Insight V1.0 subject device represents a subset of Olea Sphere® V3.0 predicate device. Therefore, the indication for use of Neuro Insight V1.0 is considered substantially equivalent to Diffusion, Perfusion, Olea Vision, Analysis and Longitudinal Analysis Mono modules of Olea Sphere® V3.0.
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# Technological Comparison
Both Neuro Insight V1.0 and Olea Sphere V3.0 have similar technological characteristics as they both:
- provide processing capabilities for the analysis of FLAIR, T1, T2, T1g, diffusion and DSC perfusion series;
- are designed to be able to process FLAIR, T1, T2, T1g, diffusion and DSC perfusion series;
- are able to provide the same outputs for FLAIR, T1, T2, T1g, diffusion and DSC perfusion metrics (CBV, CBF, MTT, TTP, Tmax/Delay, CBV_corr, K2, tMIP);
- provide the same standard viewing tools and edition of parameters that are optional inputs of compatible docker applications. Currently, with NeuroPro being the only compatible application, the only editable parameter is arterial input function (AIF) selection. As with the FDA-cleared Olea S.I.A Neurovascular V1.0 (K223532), the user can adjust the AIF automatically calculated by the application (by NeuroPro) as needed and request a recalculation of the results using the desired value. The implementation and management of this feature are exactly the same as in Olea S.I.A Neurovascular V1.0.
The minor differences in the technological characteristics between the two devices are:
- Neuro Insight V1.0 uses a motion correction algorithm based on a 3D rigid method before DSC perfusion maps computation, while Olea Sphere® V3.0 uses a 2D rigid motion correction algorithm. This difference does not impact the calculation method of the outputs. This motion correction algorithm based on a 3D rigid method has already been cleared as a component of MR Diffusion Perfusion Mismatch V1.0 (Olea Medical, France), FDA-cleared (K223502).
- Neuro Insight V1.0 uses a brain extraction tool (BET) based on a 3D deep learning algorithm before DSC perfusion maps computation, while Olea Sphere® V3.0 uses thresholds based on a histogram analysis of the MR images. For more information about this deep learning testing and validation process please refer to "About Deep learning algorithm for BET" below. This difference does not impact the calculation method of the outputs.
- Neuro Insight V1.0 uses co-registration algorithms based on 3D rigid 6-dof transformation, while Olea Sphere® V3.0 uses IPP IOP DICOM tags to locate and align volumes.
However, these minor differences in the technological characteristics between both devices do not raise different questions of safety and effectiveness.
# About Deep learning algorithm for BET
To filter out the brain and the cerebrospinal fluid (CSF), surrounding noise and background pixels on raw images, MR DSC Perfusion includes a brain extraction algorithm for MR PWI series. This brain extraction algorithm uses a 3D U-Net architecture, consisting of 6 layers (16, 32, 64, 128, 256, 512), and was optimized using both DICE and Tversky metrics. It was trained with 362 manually annotated MR volumes split in train (199 cases), validation (63 cases) and test (100 cases) dataset. The database was sourced to ensure broad representativeness depending on the manufacturer, magnetic field, acquisition parameters, origin, patient age and sex. The manual segmentation was performed by expert clinicians following criteria defined by a US board certified neuroradiologist. Two labels were used: one for the brain tissue and one for the voxels who do not belong to brain tissue (background).
Cases were collected from multiple MRI system manufacturers: 114 cases from GE Healthcare (48% at 1.5T, 52% at 3T), 127 from Siemens (64% at 1.5T, 36% at 3T), 95 from Philips (70% at 1.5T, 30% at 3T), 25 from Canon formerly Toshiba (60% at 1.5T, 40% at 3T), and one case with unknown manufacturer information due to severe DICOM anonymization.
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Patient demographics comprised 51% male subjects, 43% female subjects, with 6% lacking gender information due to DICOM anonymization protocols. Age information was limited due to anonymization processes, with over half of the dataset missing age data. Among available cases, the mean age was 60 years with a range spanning from 14 to 100 years, representing a diverse patient population across different age groups.
Ground truth brain masks were created by experienced clinicians following a standardized annotation protocol defined by a U.S. board-certified neuroradiologist. The protocol included all brain structures—hemispheres and lesions—while explicitly excluding non-brain anatomical elements such as the skull, eyeballs, and optic nerves. Each segmentation was reviewed by a neuroradiologist and a research engineer to ensure consistency and accuracy across the dataset.
A 5-fold cross-validation procedure was applied to assess performance stability and generalizability across different scanner types and patient profiles.
The achieved average DICE coefficient of 0.97, ranging from 0.907 to 0.988, exceeds the predetermined acceptance threshold of 0.95. These results demonstrate excellent spatial overlap between automated segmentations and expert-annotated ground truth masks, as well as high segmentation accuracy and consistent reliability across diverse clinical scenarios.
These conclusions confirm the algorithm's robustness and reliability, enabling accurate and reproducible brain extraction as part of automated neuroimaging workflows.
## Non-Clinical and/or Clinical Tests Summary & Conclusions
Olea Medical has conducted validation testing of the Neuro Insight V1.0. Internal verification, usability and validation testing confirms that the product specifications are met, and support of the substantial equivalence of the intended use and technological characteristics to the predicate device.
Neuro Insight V1.0 has been validated to ensure that the system, as a whole, provides all the capabilities necessary to operate according to its intended use and in a manner substantially equivalent to the predicate device.
The following performance evaluations were conducted:
- Product risk assessment;
- Software modules verification tests;
- Usability assessment;
- Software validation test.
All software features of Neuro Insight V1.0 have undergone verification and usability testing to ensure proper performance and safe integration into clinical workflows. Specific attention was given to features identified through risk analysis, which were evaluated with consideration of human factors. Testing was performed in alignment with the intended use and user instructions. No issues were reported by operators during testing, and no clinically significant failures or incidents occurred.
Based on the performance testing, the Neuro Insight V1.0 has a safety and effectiveness profile that is similar to the predicate device.
Neuro Insight V1.0 was quantitatively and qualitatively compared to Olea Sphere® V3.0 software (Olea Medical®, FDA-cleared - K152602), identified as the predicate device.
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Two main features were evaluated:
- Parametric maps computation: ADC, CBF, CBV, CBV_Corr, K2, MTT, TTP, Tmax/Delay, tMIP;
Neuro Insight V1.0 and Olea Sphere® V3.0 were quantitatively and qualitatively compared by three US board-certified neuroradiologists using 30 anonymized brain MRI cases. For each DWI and DSC parametric maps, the statistical and/or visual analysis of the results derived from this comparison supported the substantial equivalence of performance between Neuro Insight V1.0 subject device and Olea Sphere® V3.0 predicate device.
- Intra- and inter-exam co-registration: FLAIR-DWI, FLAIR-DSC, FLAIR-T1, FLAIR-T1g, FLAIR-T2, and FLAIR-follow-up FLAIR.
Neuro Insight V1.0 was qualitatively assessed by the three US board-certified neuroradiologists using 60 anonymized brain MRI cases. The visual analysis reported that all 6 co-registrations (FLAIR-DWI, FLAIR-DSC, FLAIR-T1, FLAIR-T1g, FLAIR-T2, FLAIR-follow-up FLAIR) provided by Neuro Insight V1.0 subject device were considered as acceptable for reading and interpretation.
Neuro Insight V1.0 subject device has substantially equivalent indications for use, technological characteristics, and principles of operation as Olea Sphere V3.0 predicate device. The minor technological differences between Neuro Insight V1.0 and its predicate device raise no new questions of safety or effectiveness, as the user confirmation feature is included in the reference device which was cleared for the same intended use. The methods for verification and validation testing of the subject device are well-supported in this regulation and by the predicate and reference devices' clearances, and data from such testing demonstrates the device's safety and performance.
Thus, Neuro Insight V1.0 is substantially equivalent to predicate Olea Sphere V3.0.
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With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.