Imbio CAC Software is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. Imbio CAC Software uses machine learning to analyze non-contrast thoracic CT images and outputs a summary report containing Agatston score, arterial age, and calcified lesion mass and volume metrics of the calcification burden for the whole heart and individual coronary artery level. Additionally, Imbio CAC Software outputs annotated images previewing the segmentation of calcifications for informational purposes only. Imbio CAC Software is limited to the quantification of detected possible calcifications in adult patients ≥ 29 years of age. It does not diagnose coronary artery disease. The device output will be available to the users as part of the standard DICOM viewing workflow. The Imbio CAC Software results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of CT images.
Device Story
Imbio CAC Software is a post-processing SaMD that analyzes non-contrast thoracic CT DICOM datasets to quantify coronary artery calcification. It utilizes machine learning algorithms to perform automated segmentation of calcifications in the coronary arteries (RCA, LAD, LCx). The software outputs a summary PDF report containing Agatston scores, arterial age, and calcified lesion mass and volume, alongside annotated DICOM images for informational purposes. It is intended for use in hospitals and clinics by radiologists or clinicians within standard DICOM viewing workflows. The device does not interface directly with CT scanners; it processes previously acquired images. It serves as an aid to support physicians in analyzing CT images; it does not provide a diagnosis or serve as a basis for clinical decision-making. The software benefits patients by providing automated quantification of calcification burden, assisting in the assessment of coronary artery disease risk.
Clinical Evidence
Retrospective, multi-center, standalone performance assessment using 500 anonymized chest CT series (ECG-gated and non-gated). Ground truth established by experienced technologists using an FDA-cleared semi-automated CAC scoring software. Primary endpoint was cardiovascular disease risk category agreement. Results showed a Cohen's kappa of 0.907 (95% CI 0.895, 0.920) for 5-category risk assessment, exceeding the acceptance criterion of > 0.859.
Technological Characteristics
Software-only medical device (SaMD). Operates on thoracic CT DICOM datasets (low/standard dose, cardiac-gated and non-gated, up to 3mm slice thickness). Uses machine learning for automated calcium segmentation and quantification. Default threshold 130 HU. Outputs include DICOM reports and annotated images. Moderate level of concern.
Indications for Use
Indicated for adult patients ≥ 29 years of age to evaluate calcified plaques in coronary arteries as a risk factor for coronary artery disease using non-contrast thoracic CT images. Not for diagnostic use.
Regulatory Classification
Identification
A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
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June 13, 2023
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo includes the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" and "ADMINISTRATION" in blue text.
Imbio, Inc. % Lauren Keith Director of Engineering 1015 Glenwood Avenue, Floor 4 MINNEAPOLIS MN 55405
Re: K230112
Trade/Device Name: CAC Software Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: May 9, 2023 Received: May 9, 2023
Dear Lauren Keith:
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 (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 located 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.
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 of medical device-related adverse events) (21 CFR 803) for
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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/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-device-advice-comprehensive-regulatoryassistance/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.
Lu Jiang
Lu Jiang, Ph.D. Assistant Director Diagnostic X-ray Systems Team DHT8B: Division of 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: 06/30/2020 |
| See PRA Statement below. |
| 510(k) Number (if known) | K230112 |
|--------------------------|---------|
|--------------------------|---------|
| Device Name | CAC Software |
|-------------|--------------|
|-------------|--------------|
Imbio CAC Software is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. Imbio CAC Software uses machine learning to analyze non-contrast thoracic CT images and outputs a summary report containing Agatston score, arterial age, and calcified lesion mass and volume metrics of the calcification burden for the whole heart and individual coronary artery level. Additionally, Imbio CAC Software outputs annotated images previewing the segmentation of calcifications for informational purposes only. Imbio CAC Software is limited to the quantification of detected possible calcifications in adult patients ≥ 29 years of age. It does not diagnose coronary artery disease. The device output will be available to the users as part of the standard DICOM viewing workflow. The Imbio CAC Software results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of CT images.
| Type of Use ( <i>Select one or both, as applicable</i> ) | | |
|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <table style="border:none"><tr><td><div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input checked="true" type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Prescription Use (Part 21 CFR 801 Subpart D)</div> </div></td><td><div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Over-The-Counter Use (21 CFR 801 Subpart C)</div> </div></td></tr></table> | <div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input checked="true" type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Prescription Use (Part 21 CFR 801 Subpart D)</div> </div> | <div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Over-The-Counter Use (21 CFR 801 Subpart C)</div> </div> |
| <div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input checked="true" type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Prescription Use (Part 21 CFR 801 Subpart D)</div> </div> | <div style="display:inline-block; vertical-align:middle;"> <div style="display:inline-block; vertical-align:middle;"> <input type="checkbox"/> </div> <div style="display:inline-block; vertical-align:middle;">Over-The-Counter Use (21 CFR 801 Subpart C)</div> </div> | |
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FORM FDA 3881 (7/17)
Indications for Use (Describe)
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# 510(k) Summary
## K230112
## 1.1 Submission Owner and Correspondent
- Imbio, Inc. 1015 Glenwood Avenue Floor 4 Minneapolis, MN 55405 Contact: William McLain Phone: 717-656-9656 E-Mail: billmclain@imbio.com
Other submissions correspondents: Lauren Keith, Director of Engineering, and Kai Ludwig, Senior Imaging Scientist.
## 1.2 Date Summary Prepared
January 13, 2023
### Device Trade Name 1.3
CAC Software
#### 1.4 Device Common Name
Automated computer-assisted coronary artery calcification and reporting software
## 1.5 Device Classification Name
Computed tomography x-ray system. Classified as Class 2 at 21 CFR 892.1750, product code JAK.
## 1.6 Legally Marketed Device To Which The Device Is Substantially Equivalent
The CAC Software is substantially equivalent to the Zebra Medical Vision HealthCCSng cleared under K210085.
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## Description of the Device 1.7
The Imbio CAC Software is a set of medical image post-processing computer algorithms that together performs automated coronary artery calcification segmentation and reports a total Agatston score, calcified lesion mass and volume, and arterial age from thoracic computed tomography (CT) images. The Agatston score, calcified lesion mass and volume are reported both as a total and for each of the following individual coronary arteries: right coronary artery (RCA), left anterior descending (LAD), left circumflex (LCx). The Imbio CAC Software is a single command-line executable program that may be run directly from the command-line or through scripting and thus the user interface is minimal.
Imbio CAC Software is a Software and Medical Device (SaMD) intended to provide annotated DICOM-formatted images and a PDF report that will be read most typically at a PACS workstation. Imbio CAC Software is an aid only used to support a physician in the analysis of CT images.
The Imbio CAC Software program reads in thoracic CT DICOM datasets, processes the data, then writes output DICOM files and summary reports to a specified directory. Imbio CAC Software outputs DICOMs of the original input DICOM CT images overlaid with color-codings representing the coronary artery calcification segmentations. Additionally, a summary PDF report is output.
Imbio CAC Software does not interface directly with any CT scanner or data collection equipment; instead the software imports data previously generated by such equipment and is integrated as part of the radiological workflow, reducing the risk of use errors.
## 1.8 Indication for Use
Imbio CAC Software is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. Imbio CAC Software uses machine learning to analyze non-contrast CT images and outputs a summary report containing Agatston score, arterial age, and calcified lesion mass and volume metrics of the calcification burden for the whole heart and individual coronary artery level. Additionally, Imbio CAC Software outputs annotated images previewing the segmentation of calcifications for informational purposes only. Imbio CAC Software is limited to the quantification of detected possible calcifications in adult patients > 29 years of age. It does not diagnose coronary artery disease. The device output will be available to the users as part of the standard DICOM viewing workflow. The Imbio CAC Software results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of CT images.
## 1.9 Technological Characteristics
Table 1.1 compares the technological characteristics between the proposed CAC Software and the predicate Zebra Medical Vision HealthCCSng.
Table 1.1: Technological Characteristics Comparison with Predicate Device
| Indications for Use | Due to the length of the<br>statement, see below. | Due to the length of the<br>statement, see below. | Different but does not<br>introduce questions of<br>safety and effectiveness. |
|---------------------|---------------------------------------------------|---------------------------------------------------|-------------------------------------------------------------------------------|
|---------------------|---------------------------------------------------|---------------------------------------------------|-------------------------------------------------------------------------------|
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| Characteristic | Proposed Device CAC Software | Predicate Device Zebra Medical Vision HealthCCSng | Comparison |
|------------------------------|-----------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|
| Regulatory | | | |
| FDA Clearance | TBD | K210085 (9/9/2021) | |
| Product Code | JAK | JAK | Same |
| Class | II | II | Same |
| Regulation | 21 CFR 892.1750 | 21 CFR 892.1750 | Same |
| Software | Device is software only | Device is software only | Same |
| Level of Concern | Moderate | Moderate | Same |
| General | | | |
| Modality | CT | CT | Same |
| Anatomical Site | Thoracic, Chest, Cardiac | Thoracic, Chest, Cardiac | Same |
| Support Input CT Scan | Low and standard dose. Cardiac-gated and non-cardiac-gated. Up to 3mm slice thickness. | Low and standard dose. Non-cardiac-gated. Up to 3mm slice thickness. | Different - Predicate is not labeled for use in cardiac-gated scans. |
| Image Format | DICOM | DICOM | Same |
| Use Environment | Hospitals and Clinics including Inpatient and outpatient, and lung cancer screening programs. | Hospitals and Clinics including Inpatient and outpatient, and lung cancer screening programs. | Same |
| Quantification | | | |
| Calcium Detection | Automatic | Automatic | Same |
| Default Threshold | 130 (HU) | 130 (HU) | Same |
| Calcium Reporting | CAC score and reference 5 category CAC risk | 3 category CAC risk | Different - Predicate does not report CAC score and combines lower risk categories. |
| Display and Outputs | | | |
| Outputs | DICOM Report and CAC annotated DICOM images. | DICOM Report and CAC annotated DICOM images. | Same |
| Alteration of original image | No | No | Same |
| Image Viewing | Images viewed on existing viewing workstation. | Images viewed on existing viewing workstation. | Same |
| Characteristic | Proposed Device<br>CAC Software | Predicate Device<br>Zebra Medical Vision<br>HealthCCSng | Comparison |
| Communication with Patient | Does not communicate<br>with patients. | Does not communicate<br>with patients. | Same |
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Proposed Device CAC Software Indication for Use: Imbio CAC Software is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. Imbio CAC Software uses machine learning to analyze non-contrast thoracic CT images and outputs a summary report containing Agatston score, arterial age, and calcified lesion mass and volume metrics of the calcification burden for the whole heart and individual coronary artery level. Additionally, Imbio CAC Software outputs annotated images previewing the segmentation of calcifications for informational purposes only. Imbio CAC Software is limited to the quantification of detected possible calcifications in adult patients ≥ 29 years of age. It does not diagnose coronary artery disease. The device output will be available to the users as part of the standard DICOM viewing workflow. The Imbio CAC Software results are not intended to be used on a stand-alone basis for clinical decision-making or otherwise preclude clinical assessment of CT images.
Predicate Device Zebra Medical Vision HealthCCSng Indications for Use: HealthCCSng device is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. The software generates an estimated coronary artery calcium detection category. The HealthCCSng device analyzes existing non-cardiac-gated CT studies that include the heart of adult patients above the age of 30. The device generates a three-category output representing the estimated quantity of calcium detected together with the preview axial images of the detected calcium meant for informational purposes only. The device output will be available to the radiologist as part of their standard workflow. The HealthCCSng results are not intended to be used on a stand-alone basis for risk attribution, clinical decision-making or otherwise preclude clinical assessment of CT studies.
## 1.10 Clinical Study
Non-clinical testing was conducted in the form of a retrospective, multi-center, standalone device performance assessment. 500 anonymized chest CT series meeting the input requirements for Imbio CAC Software were curated from a variety of sources including large publically available databases and private imaging data brokers. Exclusion criteria included:
- · CTs from pediatric patients (< 22 years old)
- · Contrast-enhanced acquisitions
- · Scans with significant respiratory motion
- · Scans with severe metal artifacts
- · Scans containing non-thoracic anatomy
The mean age of patients whose scans were included in the performance assessment was 64.3 years with a standard deviation of 10 years with the oldest and youngest patient being 90+ (not listed above 90 years old) and 29 years old, respectively. Gender distrubution was 41.7% male and 42.5 % female with 15.6% of the data having no gender information. Images originated from GE Medical Systems (65.1%), Siemens (19.4%), Imatron (15.2%), and Philips (0.2%) scanners. There was an equal split of ECG-gated and non-gated acquisitions.
All chest CT series were annotated by experienced 3D Image Post-Processing Technologists using an FDA-cleared semi-automated CAC scoring software program. These images and the corresponding CAC scores were used as ground truth for Imbio CAC Software validation.
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The primary endpoint was to evaluate the cardiovaclar disease risk category across all cases between Imbio CAC Software and the ground truth. For a 5-category risk assessment, the Cohen's kappa between Imbio CAC Software and the ground truth was 0.907 (95% CI 0.895, 0.920), which met the acceptance criteria of kappa > 0.859.
## 1.11 Biocompatibility
Biocompatibility testing is not applicable for the CAC Software.
## Conclusions 1.12
The results of the comparison of design, intended use and technological characteristics demonstrate that the device is as safe and effective as the legally marketed predicate device.
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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.
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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.
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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.
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Reading rule for every project: how many summaries do you read in full?
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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.
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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.
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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.