Archived clinical specimens were used to evaluate the precision, reproducibility, and accuracy of the Duet System in detecting ALK gene rearrangements in NSCLC tissue, and to verify performance across different hardware configurations for previously cleared indications.
Archived clinical specimens; Method comparison; Reproducibility study
Clinical Evidence
Study Design
Population
Comparator
Key Endpoints
Precision/Reproducibility Performance; Retrospective evaluation of archived clinical specimen slides; Follow-up/Duration: Not applicable
Formalin-fixed paraffin-embedded (FFPE) non-small cell lung cancer (NSCLC) tissue specimens; Sample Size: 16 archived clinical specimen slides; Number of Sites: 3
Not applicable for this study
Repeatability and reproducibility (CV%)
Analytical Performance/Methods Comparison; Retrospective method comparison; Follow-up/Duration: Not applicable
FFPE NSCLC tissue specimens; Sample Size: 113 specimen slides; Number of Sites: 3
Manual scoring method
Percent agreement with manual scoring
Configurations method comparison; Retrospective comparison of patient slides; Follow-up/Duration: Not applicable
Patient slides from four previously cleared indications (Hematopoietic, Amniotic, Bladder cancer, Breast cancer)
Cleared Duet™ configuration (version 2.5)
Concordance of final interpretation and numerical results
Indications for Use
The Duet™ System is an automated scanning microscope and image analysis system. It is intended for in-vitro diagnostic use as an aid to the pathologist in the detection, classification and counting of cells of interest based on color, intensity, size, pattern and shape. The Duet™ System is intended to: 1. Detect Hematopoietic cells stained by Giemsa stain, Immunohistochemistry or ISH (with brightfield and fluorescent) prepared from cell suspension. 2. Detect Amniotic cells stained by FISH (using direct labeled DNA probes for chromosomes X,Y,13, 18 and 21). 3. Detect Aneuploidy for chromosomes 3,7, 17 and loss of the 9p21 locus via FISH in Urine specimens from subjects with transitional cell carcinoma of the bladder, probed by the Vysis Urovysion Bladder Cancer Kit. 4. Detect and quantify chromosome 17 and the HER-2/neu gene via fluorescence in situ hybridization (FISH) in interphase nuclei from formalin-fixed, paraffin embedded human breast cancer tissue specimens, probed by the Vysis® Path Vysion™ HER-2 DNA Probe Kit. The Duet™ is to be used as an adjunctive automated enumeration tool, in conjunction with manual review of the digital image, to assist in determining HER-2/neu gene to chromosome 17 signal ratio. 5. Qualitatively detect rearrangements involving the ALK gene via fluorescence in situ hybridization (FISH) in formalin-fixed paraffin-embedded (FFPE) non-small cell lung cancer (NSCLC) tissue specimens, probed with the Vysis ® ALK Break Apart FISH Probe Kit. The Duet™ is to be used as an adjunctive automated enumeration tool, in conjunction with manual review of the digital image. Note: The pathologist should verify the image analysis software application score.
Device Story
Duet™ System is an automated scanning microscope and image analysis workstation; integrates microscope, CCD camera, motorized stage, computer, and software. Input: FFPE NSCLC tissue slides hybridized with Vysis® ALK Break Apart FISH Probe Kit. Operation: System scans slides in high-resolution brightfield and fluorescence; automated algorithm detects fusion signals and non-fused orange/green signals; suggests cell classification. Output: Automated enumeration of positive/negative cells and percentages; digital images for pathologist review. Usage: Clinical laboratory setting; operated by trained personnel; pathologist confirms results via manual review of digital images. Benefit: Standardizes and accelerates FISH signal enumeration; assists in determining ALK gene rearrangement status for NSCLC patients.
Clinical Evidence
Bench testing and method comparison study. 113 FFPE NSCLC slides analyzed across three clinical sites. Compared Duet™ automated results to manual review. Overall agreement 99.1% (95% CI: 95.2% - 99.8%); negative percent agreement 100% (95% CI: 95.5% - 100%); positive percent agreement 96.9% (95% CI: 84.3% - 99.5%). Reproducibility assessed via 16-slide panel across runs, days, and sites; results showed acceptable variability for the intended use.
Technological Characteristics
Automated scanning microscope; CCD camera; motorized stage; PC workstation. Software version 3.5. Connectivity: Barcode reader for specimen ID. Imaging: High-resolution brightfield and fluorescent illumination. Hardware includes 22" high-resolution LED touch-screen display and automated slide loaders (up to 200 slides).
Indications for Use
Indicated for use as an adjunctive automated FISH enumeration tool for pathologists to detect, classify, and count cells in FFPE NSCLC tissue specimens to identify ALK gene rearrangements, in conjunction with manual review of digital images.
Regulatory Classification
Identification
An automated FISH enumeration system is a device that consists of an automated scanning microscope, image analysis system, and customized software applications for FISH assays. This device is intended for in vitro diagnostic use with FISH assays as an aid in the detection, counting and classification of cells based on recognition of cellular color, size, and shape, and in the detection and enumeration of FISH signals in interphase nuclei of formalin-fixed, paraffin-embedded human tissue specimens.
Special Controls
The device is classified as Class II under regulation 21 CFR 866.4700 with special controls. The special control guidance document " Class II Special Controls Guidance Document: Automated Fluorescence in situ Hybridization (FISH) Enumeration Systems" is available at www.fda.gov/cdrh/oivd/guidance/1550.pdf.
*Classification.* Class II (special controls). The special control is FDA's guidance document entitled “Class II Special Controls Guidance Document: Automated Fluorescence*in situ* Hybridization (FISH) Enumeration Systems.” See § 866.1(e) for the availability of this guidance document.
Predicate Devices
Duet™ System (k030192, k040591, k050840, k061602)
Submission Summary (Full Text)
{0}
1
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
A. 510(k) Number:
k130775
B. Purpose for Submission:
Expansion of the Duet™ System applications to include the automated FISH detection and enumeration of gene rearrangements involving the ALK gene.
Modification of the Duet™ system from its previous configuration (Version 2.5) to contain an updated camera, display and slide loader in Version 3.5.
C. Manufacturer and Instrument Name:
Bioview, Ltd.
Duet™ System
D. Type of Test or Tests Performed:
As an adjunctive automated FISH enumeration tool, in conjunction with manual review of the digital image.
E. System Descriptions:
1. Device Description:
The Duet™ System is an automated scanning microscope and image analysis system. The Duet™ System workstation integrates a microscope, CCD camera, motorized stage, computer, keyboard, mouse, joystick, monitor and a dedicated software program. The Duet™ System scans cell samples in high resolution and in full color at high speed both in bright light and fluorescent illumination. The Duet™ System suggests classification of the cells according to their morphological features, their staining and fluorescent signals and allows the user to examine the results, correct them as needed and generate a report summarizing the sample’s data.
This particular Duet™ system application is an accessory to h the Vysis® ALK Break Apart FISH Probe Kit.
2. Principles of Operation:
Samples are prepared according the instructions for the Vysis® ALK Break Apart FISH Probe kit. The user selects the appropriate areas for analysis in accordance with the ALK kit instructions. The Duet™ System automatically captures images for each of the selected areas. The user is instructed to select the cells for analysis, according the ALK kit instructions. An automatic algorithm detects fusion signals and non-fused orange and green signals in each cell and suggests a classification for the cell. The user is instructed to review the signal enumeration for all relevant cells. The total number of positive cells, negative cells and their percentage are automatically calculated and presented to the user. A pathologist confirms the calculated results by manual review of the digital image. In
{1}
the case of an equivocal sample (10 to 50% positive), additional cells are selected and analyzed. The mean of the two analyses will determine the final sample score.
3. Modes of Operation:
Semi-automated computer assisted interpretation
4. Specimen Identification:
Barcode reader
5. Specimen Sampling and Handling:
Specimens are FFPE NSCLC tissue specimens on glass slides hybridized with the Vysis® ALK Break Apart FISH Probe kit.
6. Calibration:
The system requires periodic calibration which should be performed only by BioView authorized personnel.
7. Quality Control:
Control slides are prepared and run concurrently with patient slides according to the Vysis® ALK BREAK Apart Kit instructions. The control slides are tested on the Duet™ System according to the same procedure as patient slides. It is the responsibility of the pathologist to assure the control slides meet quality acceptance criteria.
8. Software:
FDA has reviewed applicant’s Hazard Analysis and Software Development processes for this line of product types:
Yes ☐ x ☐ or No ☐
F. Regulatory Information:
1. Regulation section:
21 CFR §866.4700 – Automated fluorescence *in situ* hybridization (FISH) enumeration systems
2. Classification:
Class II
3. Product code:
{2}
NTH – system, automated scanning microscope and image analysis for fluorescence *in situ* hybridization (FISH) assays
4. Panel:
Pathology (88)
G. Intended Use:
1. Indication(s) for Use:
The Duet™ System is an automated scanning microscope and image analysis system. It is intended for in-vitro diagnostic use as an aid to the pathologist in the detection, classification and counting of cells of interest based on color, intensity, size, pattern and shape.
The Duet™ System is intended to:
- Detect Hematopoietic cells stained by Giemsa stain, Immunohistochemistry or ISH (with brightfield and fluorescent) prepared from cell suspension.
- Detect amniotic cells stained by FISH (using direct labeled DNA probes for chromosomes X, Y, 13, 18 and 21).
- Detect aneuploidy for chromosomes 3, 7, 17 and loss of the 9p21 locus via FISH in urine specimens from subjects with transitional cell carcinoma of the bladder, probed by the Vysis Urovysion™ Bladder Cancer Kit.
- Detect and quantify chromosome 17 and the HER-2/neu gene via fluorescence *in situ* hybridization (FISH) in interphase nuclei from formalin-fixed, paraffin embedded human breast cancer tissue specimens, probed by the Vysis® PathVysion™ HER-2 DNA Probe Kit. The Duet™ is to be used as an adjunctive automated enumeration tool, in conjunction with manual review of the digital image, to assist in determining HER-2/neu gene to chromosome 17 signal ratio.
- Qualitatively detect rearrangements involving the ALK gene via fluorescence *in situ* hybridization (FISH) in formalin-fixed paraffin-embedded (FFPE) non-small cell lung cancer (NSCLC) tissue specimens, probed with the Vysis® ALK Break Apart FISH Probe Kit. The Duet™ is to be used as an adjunctive automated enumeration tool, in conjunction with manual review of the digital image.
Note: The pathologist should verify the image analysis software application score.
2. Special Conditions for Use Statement(s):
For prescription use only.
H. Substantial Equivalence Information:
1. Predicate Device Name(s) and 510(k) numbers:
BioView Duet™ System, k061602
{3}
2. Comparison with Predicate Device:
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Specimen Type | Formalin-fixed paraffin-embedded non-small cell lung cancer (NSCLC) tissue specimens | Formalin-fixed paraffin-embedded (FFPE) breast cancer tissue specimens |
| Method of cell detection | Colorimetric pattern recognition by microscopic examination of prepared cells by size, shape, and intensity of counterstained nuclei as observed by an automated computer controlled microscopic and/or visual observation by a health care professional. | Same |
| Detection Method | Fluorescence in situ hybridization (FISH) | Same |
| Intended Use | Automated scanning microscope and image analysis system. It is intended for in vitro diagnostic use as an aiding tool to the pathologist in the detection, classification and counting of cells of interest based on color, intensity, size, pattern and shape. | Same |
| Device components | • PC workstation
• Camera
• Monitor
• Microscope
• Motorized Stage
• Software | Same |
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Probe Kit | Vysis® ALK Break Apart FISH Probe Kit | Vysis® PathVysion™ HER-2 DNA Probe Kit |
| Slide Capacity | Up to 200 slides | Up to 8 slides |
| Software Version | 3.5 | 2.5 |
| Camera | DAGE-MTI Excel | Sony DXC900 and JVC KY0F75U color 3CCD |
{4}
| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Display | • 22” High Resolution LED Display
• Touch-screen high resolution LED display with a pen pointing-device | 17” High resolution LCD Display |
| Slide Loader | • “Accord Plus” (single slide stage configuration).
• “Allegro Plus” (8-slide stage configuration);
• “Duet-3” (50 slide loader configuration);
• “Encore” (200 slide loader configuration) | • “Accord Plus” (single slide stage configuration).
• “Allegro Plus” (8-slide stage configuration); |
I. Special Control/Guidance Document Referenced (if applicable):
Guidance for Industry and FDA Staff – Class II Special Controls Guidance Document: Automated Fluorescence in situ Hybridization (FISH) Enumeration Systems
Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices
J. Performance Characteristics:
1. Analytical Performance:
a. Accuracy:
Slides containing formalin-fixed paraffin-embedded (FFPE) tissue specimens from patients with non-small cell lung cancer (NSCLC) were hybridized with the FDA approved Vysis® ALK Break Apart FISH Probe Kit according to the manufacturer’s instructions.
Each site was asked to prepare at least 30 slides from which at least 8 slides should be either equivocal or positive. The slides were taken from archived slides that were previously counted and analyzed manually. The staff was guided that the slides were selected in consecutive order.
At three clinical sites, a total of 113 slides including 12 cases in the equivocal zone were analyzed. Method comparison results for all three sites combined are presented below in Table 1:
{5}
Table 1: Method Comparison of Duet™ System vs. Manual Method- All sites combined
| | Manual Method | | | |
| --- | --- | --- | --- | --- |
| | | Negative | Positive | Total |
| Duet Method | Negative | 81 | 1 | 82 |
| | Positive | 0 | 31 | 31 |
| | Total | 81 | 32 | 113 |
Overall agreement: $99.1\%$ (95% CI: 95.2% - 99.8%)
Negative percent agreement: $100\%$ (95% CI: 95.5% - 100%)
Positive percent agreement: $96.9\%$ (95% CI: 84.3% - 99.5%)
# b. Precision/Reproducibility:
A panel of 16 archived clinical specimen slides (spanning 4 value ranges: $< 10\%$ , 10-25%, $>25 - 50\%$ and $>50\%$ ) were chosen to establish device within-run, between day and between site variability.
Within-run: Three runs for each of the panel members were performed on the same day.
| Slide ID | Mean | Standard Deviation | Coefficient of Variation (%) |
| --- | --- | --- | --- |
| CYNK-40 | 2.0 % | 0.0 | 0.0 |
| CYNK-63 | 3.3% | 1.2 | 34.6 |
| CYNK-64 | 1.3 % | 1.2 | 86.6 |
| CYNK-65 | 4.0 % | 2.0 | 50.0 |
| CYNK-49 | 7.3% | 1.2 | 15.7 |
| CYNK-53 | 12.3% | 1.5 | 12.4 |
| CYNK-55 | 6.7% | 1.2 | 17.3 |
| CYNK-67 | 16.0% | 1.0 | 6.3 |
| BV Val 13 | 48.7% | 9.2 | 19.0 |
| BV Val 07 | 50.7% | 8.1 | 16.1 |
| BV Val 11 | 34.0% | 3.0 | 8.8 |
| CYNK-41 | 30.3% | 4.0 | 13.3 |
| BV Val 09 | 74.7% | 4.2 | 5.6 |
| BV Val 10 | 57.3% | 4.2 | 7.3 |
| CYNK-36 | 69.3% | 5.8 | 8.3 |
| CYNK-50 | 53.0% | 8.5 | 16.1 |
{6}
Between-day: Variability was assessed by assessing panel member performance on three different days. The shortest between-day interval was five days.
| Slide ID | Mean | Standard Deviation | Coefficient of Variation (%) |
| --- | --- | --- | --- |
| CYNK-57 | 3.0 % | 5.2 | 173.2 |
| CYNK-63 | 2.0% | 2.0 | 100.0 |
| CYNK-64 | 0.7 % | 1.2 | 173.2 |
| CYNK-65 | 2.7 % | 1.2 | 43.3 |
| CYNK-53 | 14.0% | 0.0 | 0.0 |
| CYNK-67 | 15.7% | 1.2 | 7.4 |
| CYNK-69 | 10.3% | 3.5 | 34.0 |
| CYNK-70 | 10.7% | 2.1 | 19.5 |
| BV Val 13 | 56.7% | 3.1 | 5.4 |
| BV Val 07 | 51.0% | 5.6 | 10.9 |
| BV Val 11 | 40.0% | 10.8 | 27.0 |
| CYNK-47 | 29.3% | 3.1 | 10.4 |
| BV Val 03 | 64.7% | 3.1 | 4.7 |
| BV Val 06 | 55.3% | 3.1 | 5.5 |
| BV Val 09 | 70.0% | 12.0 | 17.1 |
| CYNK-50 | 52.3% | 7.5 | 14.3 |
Site-to-Site: Reproducibility was validated by testing each slide three times, each at a different site and Duet system.
| Slide ID | Mean | Standard Deviation | Coefficient of Variation (%) |
| --- | --- | --- | --- |
| CYNK-57 | 4.0 % | 4.0 | 100.0 |
| CYNK-63 | 4.0% | 0.0 | 0.0 |
| CYNK-64 | 3.7 % | 3.2 | 87.7 |
| CYNK-65 | 3.3 % | 1.2 | 34.6 |
| CYNK-53 | 12.0% | 2.0 | 16.7 |
| CYNK-55 | 10.3% | 2.1 | 20.1 |
| CYNK-67 | 20.3% | 4.2 | 20.5 |
| CYNK-69 | 9.7% | 0.6 | 6.0 |
| BV Val 07 | 44.0% | 1.7 | 3.9 |
| BV Val 11 | 36.7% | 2.5 | 6.9 |
| CYNK-41 | 35.0% | 4.6 | 13.1 |
| CYNK-47 | 35.0% | 5.0 | 14.3 |
| BV Val 06 | 58.7% | 3.1 | 5.2 |
| BV Val 09 | 76.7% | 8.3 | 10.9 |
| BV Val 10 | 55.3% | 2.3 | 4.2 |
| BV Val 02 | 79.3% | 12.9 | 16.2 |
c. Linearity:
Not applicable.
{7}
d. Carryover:
Not applicable.
e. Interfering Substances:
Not applicable.
2. Other Supportive Instrument Performance Data Not Covered Above:
A number of probes (intended use points 1-4) were previously cleared for use with device version 2.5. In order to determine whether the performance of these probes on device version 3.5 has been impacted, additional technical descriptions and performance data were reviewed comparing performance of the two instrument versions. The additional technical descriptions and performance data were sufficient to demonstrate that device performance has not been impacted by the instrument version change.
K. Proposed Labeling:
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
L. Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
8
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
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.
How do you verify an AI chat answer on the device detail page?
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.
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.