Bunkerhill AAQ is a radiological image processing system software indicated for use in the analysis of CT exams with or without contrast, that include the L1 – L5 region of the abdominal aorta, in adults aged 22 and older. The device is intended to assist appropriately trained medical specialists by providing the user with the maximum axial abdominal aortic diameter measurement of cases that include the abdominal aorta. Bunkerhill AAQ is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas. The Bunkerhill AAQ results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a qualified interpreting physician. For final clinically approved measurements, please refer to the official radiology report. Clinicians are responsible for viewing full images per the standard of care.
Device Story
Software-only device; processes axial CT scans (with/without contrast) of abdomen/pelvis. Receives DICOM instances; uses deep learning algorithms to automatically identify and measure maximum abdominal aortic diameter. Operates on cloud server; results exported as DICOM to PACS. Produces preview image with diameter annotation; original unmarked series remains available. Used in medical facilities by trained specialists. Provides adjunctive, unofficial measurements; requires physician review of full images and clinical context for final diagnosis. Benefits include automated measurement assistance to support clinical workflow.
Clinical Evidence
Retrospective study (n=258) comparing device output to ground truth established by 3 U.S. Board Certified Radiologists. Population: median age 67 (range 22-99), balanced gender. Mean absolute error = 1.58 mm (95% CI 1.38–1.80), meeting the ≤ 2.0 mm acceptance criterion. Secondary endpoint ΔICC = 0.003 (< 0.05). Bland-Altman limits ± ≈ 5 mm. Subgroup analyses confirmed consistent performance across sex, age, aneurysm size, manufacturer, slice thickness, kVp, and contrast/non-contrast status.
Technological Characteristics
Software-only; cloud-hosted. Deep learning algorithm. Inputs: DICOM CT images (with/without contrast). Outputs: Annotated preview image and measurement data. Interoperability: DICOM standard. No hardware components.
Indications for Use
Indicated for adults aged 22+ undergoing CT exams (with or without contrast) of the L1-L5 abdominal aorta region. Used to evaluate normal and aneurysmal abdominal aortas; not for post-operative aortas.
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
BunkerHill Health
% John Smith, JD Partner
Hogan Lovells US, L.L.P.
555 Thirteenth Street NW,
WASHINGTON, DC 20004
July 1, 2025
Re: K243779
Trade/Device Name: Bunkerhill Abdominal Aortic Quantification (AAQ)
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical Image Management And Processing System
Regulatory Class: Class II
Product Code: QIH
Dated: June 2, 2025
Received: June 2, 2025
Dear John 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.
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"
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K243779 - John Smith
Page 2
(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.
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
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K243779 - John Smith
Page 3
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,
Jessica Lamb
Assistant Director
Imaging Software Team
DHT8B: Division of Radiologic Imaging
Devices and Electronic Products
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)
K243779
Device Name
Bunkerhill Abdominal Aortic Quantification (AAQ)
Indications for Use (Describe)
Bunkerhill AAQ is a radiological image processing system software indicated for use in the analysis of CT exams with or without contrast, that include the L1 – L5 region of the abdominal aorta, in adults aged 22 and older.
The device is intended to assist appropriately trained medical specialists by providing the user with the maximum axial abdominal aortic axial diameter measurement of cases that include the abdominal aorta. Bunkerhill AAQ is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas.
The Bunkerhill AAQ results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a qualified interpreting physician. For final clinically approved measurements, please refer to the official radiology report. Clinicians 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)
## CONTINUE ON A SEPARATE PAGE IF NEEDED.
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K243779
510(K) SUMMARY
Bunkerhill AAQ
K243779
Bunkerhill, Inc.
436 Bryant Street
San Francisco CA 94107
Phone: (408) 8028146
Contact Person: Eren Alkan
Date Prepared: July 1, 2025
## Proposed Device
| Proprietary Name | Bunkerhill Abdominal Aortic Quantification (AAQ) |
| --- | --- |
| Classification Name | Medical image management and processing system |
| Regulation Number | 21 CFR 892.2050 |
| Product Code | QIH |
| Regulatory Class | II |
## Predicate Device
| Proprietary Name | Briefcase Quantification Device |
| --- | --- |
| Premarket Notification | K230534 |
| Classification Name | Medical image management and processing system |
| Regulation Number | 21 CFR 892.2050 |
| Product Code | QIH |
| Regulatory Class | II |
## Device Description
Bunkerhill AAQ is a software-only medical device that employs deep learning algorithms to provide automatic maximal abdominal aortic diameter measurements from axial CT scans of the abdomen/pelvis, with or without IV contrast.
Bunkerhill AAQ receives DICOM instances and processes them chronologically by running the algorithm on relevant series to measure the maximum abdominal aortic diameter. Following the AI processing, the output of the algorithm analysis is transferred to standard radiology image review and reporting software.
Bunkerhill AAQ produces a preview image annotated with the maximum axial diameter measurement. The diameter marking is not intended to be a final output, but serves the purpose of visualization and measurement. The original, unmarked series remains available in the PACS as well.
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The preview image presents an unofficial and not final measurement, and the user is instructed to review the full image and any other clinical information before making a clinical decision. The image includes a disclaimer: "Not for diagnostic use. The measurement is unofficial, not final, and must be reviewed by a qualified interpreting physician".
# Intended Use / Indications for Use
Bunkerhill AAQ is a radiological image processing system software indicated for use in the analysis of CT exams with or without contrast, that include the L1 - L5 region of the abdominal aorta, in adults aged 22 and older.
The device is intended to assist appropriately trained medical specialists by providing the user with the maximum axial abdominal aortic diameter measurement of cases that include the abdominal aorta. Bunkerhill AAQ is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas.
The Bunkerhill AAQ results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a qualified interpreting physician. For final clinically approved measurements, please refer to the official radiology report. Clinicians are responsible for viewing full images per the standard of care.
A table comparing the intended use of the subject and predicate devices is provided below.
| | Proposed Device: Bunkerhill AAQ Algorithm | Predicate Device: Briefcase Quantification (K230534) |
| --- | --- | --- |
| Intended use / Indications for use | Bunkerhill AAQ is a radiological image processing system software indicated for use in the analysis of CT exams with or without contrast, that include the L1 – L5 region of the abdominal aorta, in adults aged 22 and older. The device is intended to assist appropriately trained medical specialists by providing the user with the maximum axial abdominal aortic diameter measurement of cases that include the abdominal aorta. Bunkerhill AAQ is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas. | BriefCase-Quantification is a radiological image management and processing system software indicated for use in the analysis of CT exams with contrast, that include the abdominal aorta, in adults or transitional adolescents aged 18 and older. The device is intended to assist appropriately trained medical specialists by providing the user with the maximum abdominal aortic axial diameter measurement of cases that include the abdominal aorta (M-AbdAo) BriefCase-Quantification is indicated to evaluate normal and aneurysmal abdominal aortas and is not intended to evaluate post-operative aortas. |
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| | Proposed Device: Bunkerhill AAQ Algorithm | Predicate Device: Briefcase Quantification (K230534) |
| --- | --- | --- |
| | The Bunkerhill AAQ results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a qualified interpreting physician. For final clinically approved measurements, please refer to the official radiology report. Clinicians are responsible for viewing full images per the standard of care. | The BriefCase-Quantification results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of cases. These measurements are unofficial, are not final, and are subject to change after review by a radiologist. For final clinically approved measurements, please refer to the official radiology report. Clinicians are responsible for viewing full images per the standard of care. |
## Summary of Technological Characteristics
At a high level, the subject and predicate devices are based on the following same technological elements:
- Both the predicate and the subject device use deep-learning algorithms to assist the medical professionals with the maximum abdominal aortic axial diameter measurement.
- Both devices analyze non-gated chest computed tomography (CT) images that are sent to the software in DICOM format.
- Both devices serve as support tools to provide information to the physician. Both can be used on-demand or optionally by the physician and do not provide a definitive diagnosis. Both devices do not replace clinical evaluation and do not alter the standard of care. Both require the physician to use this information to decide next steps and/or additional diagnostic work up.
- Both devices provide a preview image annotated with the maximum axial diameter measurement and the original, unmarked series remains available in the PACS.
The following technological difference exists between the subject and predicate devices:
- Minor difference in device input (contrast and non-contrast for subject device vs contrast scans for predicate device)
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| | Proposed Device: Bunkerhill AAQ Algorithm | Predicate Device: Briefcase Quantification (K230534) | Summary |
| --- | --- | --- | --- |
| Product code | QIH | QIH | Same |
| Regulation number | 21 CFR §892. 2050 | 21 CFR §892. 2050 | Same |
| Modality | Computed tomography (CT) | Computed tomography (CT) | Same |
| Image format | DICOM | DICOM | Same |
| Supported CT scan | CT exams with or without contrast that include the abdominal aorta | CT exams with contrast that include the abdominal aorta | Similar |
| Diameter measurement | Yes | Yes | Same |
| Algorithm | Artificial intelligence algorithm with database of images. | Artificial intelligence algorithm with database of images. | Same |
| Interference with standard workflow | No | No | Same |
| Output | Output can be optionally or on-demand be inserted into the radiology report; produces a preview image annotated with the maximum axial diameter measurement. The original, unmarked series remains available in the PACS as well. | Produces a preview image annotated with the maximum axial diameter measurement. The original, unmarked series remains available in the PACS as well. | Similar |
{8}
| | Proposed Device: Bunkerhill AAQ Algorithm | Predicate Device: Briefcase Quantification (K230534) | Summary |
| --- | --- | --- | --- |
| Structure | -Bunkerhill AAQ, is hosted on a cloud server, analyzes applicable CT images that are acquired on CT scanner that are forwarded to Bunkerhill AAQ.
- The results of the analysis are exported in DICOM format, and are sent to a PACS destination for review by medical specialists, to assist in the measurement of the abdominal aorta. | -BriefCase-Quantification, is hosted on a cloud server, analyzes applicable CT images that are acquired on CT scanner that are forwarded to BriefCase-Quantification.
- The results of the analysis are exported in DICOM format, and are sent to a PACS destination for review by medical specialists, to assist in the measurement of the abdominal aorta. | Same |
| Type of Interpretation | Adjunctive information | Adjunctive information | Same |
| Intended User | Appropriately trained medical specialists | Appropriately trained medical specialists | Same |
| Patient population | Patients aged 18 years and above | Patients above the age of 18 | Same |
| Anatomical location | Abdominal aorta | Abdominal aorta | Same |
| Intended location | Medical facility | Medical facility | Same |
| Rx or OTC | Rx | Rx | Same |
## Performance Data
Safety and performance of the AAQ algorithm has been evaluated and verified in accordance with software specifications and applicable performance standards through Software Development and Validation & Verification Process to ensure performance according to specifications, User Requirements and Federal Regulations and Guidance documents, “Content of Premarket Submissions for Device Software Functions”.
{9}
The AAQ algorithm performance was validated in a stand-alone retrospective study for overall agreement of the device output compared to a ground truth established by 3 U.S. Board Certified Radiologists. The pivotal test set comprised 258 patients sourced North Carolina, Alabama, the greater Washington D.C area, and Sao Paulo, Brazil. The mean-absolute-error = 1.58 mm (95% CI 1.38–1.80) versus the ≤ 2.0 mm acceptance criterion, and the secondary endpoint with ΔICC = 0.003 < 0.05, while Bland-Altman limits were ± ≈ 5 mm, supporting the characterized performance. The dataset was balanced with 118 male and 140 female patients, the median age of the patient population was 67 years old and the range was 22 years old to 99 years old, the manufacturers represented in the test set were Toshiba, Phillips, Siemens, and GE Healthcare, and the test set consisted of 58% non-contrast studies and 42% contrast studies. The subgroup analyses showed consistent performance across sex, age, aneurysm size, manufacturer, slice-thickness strata, kVp ranges, contrast vs. non-contrast, and collection site demonstrating the generalizability of the algorithm.
## Conclusions
The Bunkerhill AAQ algorithm is as substantially equivalent as the predicate Briefcase Quantification device (K230534). The subject device has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended diagnostic use of the device and do not affect its safety and effectiveness when used as labeled. In summary, any minor differences between the AAQ algorithm and the Briefcase Quantification do not raise any issues of substantial equivalence.
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Part 1 — Search, results, and everyday workflows 16 min
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1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
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Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
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.
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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.