AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K220956 · Jul 20, 2022
Libby Echo:Prio
Dyad Medical, Inc.
Retrospective clinical dataset of cardiac ultrasound images
The device performance (view classification accuracy, heart rate estimation, and ejection fraction calculation) was evaluated using a retrospective clinical dataset to demonstrate robustness and accuracy.
Machine learning based view classification and border segmentation
—
Slope of 0.79 for Bivariate Linear Regression (BLS) with 95% CI (0.52, 0.98)
—
—
Retrospective clinical dataset
4 (human experts)
Echocardiographic View Classification
Machine learning based view classification
—
Accuracy of 97%, average F1 > 96.6%, average sensitivity 96.8%, average specificity 98.5%
—
—
Retrospective clinical dataset
—
Heartbeat Rate
Machine learning based view classification and border segmentation
—
Minimal bias (slope of 0.98 in linear regression with 95% CI)
—
—
Retrospective clinical dataset
—
Indications for Use
Libby™ Echo:Prio is software that is used to process previously acquired DICOM-compliant cardiac ultrasound images, and to make measurements on these images in order to provide automated estimation of several cardiac measurements. The data produced by this software is intended to be used to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners for clinical decision-making. Libby™ Echo:Prio is indicated for use in adult patients.
Device Story
Libby Echo:Prio is post-processing software for cardiovascular ultrasound images. Input: DICOM-compliant cardiac ultrasound clips. Operation: Machine learning-based view classification and border segmentation identify cardiac structures; software performs automated measurements including end diastole/systole frame identification, heart rate estimation, and ejection fraction (EF) calculation. Output: Quantitative cardiac measurements, automated markup, and summary reports. Usage: Medical facility; operated by sonographers and cardiologists. Workflow: Sonographer reviews automated results, performs manual edits/corrections, and generates reports for physician review. Clinical impact: Aids diagnostic review and cardiac function assessment; provides consistent, automated analysis to support clinical decision-making.
Clinical Evidence
Retrospective performance testing on a diverse clinical dataset. View classification accuracy: 97% (F1 >96.6%, Sn 96.8%, Sp 98.5%). Heart rate estimation showed minimal bias (slope 0.98, 95% CI). Ejection fraction (EF) output compared to four human experts showed a slope of 0.79 (95% CI 0.52, 0.98), within the range of typical inter-observer variation.
Technological Characteristics
Software-only device operating on off-the-shelf hardware. Uses machine learning for view classification and border segmentation. Processes DICOM-compliant ultrasound images. Standards: NEMA PS 3.1-3.20 (DICOM), IEC 62304 (software lifecycle), ISO 14971 (risk management), IEC 62366-1 (usability).
Indications for Use
Indicated for adult patients to process previously acquired DICOM-compliant cardiac ultrasound images for automated estimation of cardiac measurements to support clinical decision-making by cardiologists, sonographers, or licensed healthcare practitioners.
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).
{0}------------------------------------------------
Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services seal on the left and the FDA acronym along with the full name of the agency on the right. The FDA part of the logo is in blue, with the acronym in a square and the full name written out to the right of it.
Dyad Medical, Inc % Yervant Chijian Regulatory and Quality Consultant Pharmalex Pty Ltd Suite 10.4, 1 Chandos Street St. Leonards, NSW 2068 AUSTRALIA
Re: K220956
July 20, 2022
Trade/Device Name: Libby Echo:Prio Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: OIH Dated: June 17, 2022 Received: June 21, 2022
Dear Yervant Chijian:
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 and Part 809); medical device reporting of medical device-related adverse events) (21 CFR
{1}------------------------------------------------
803) for 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 medical devices and radiation-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,
Jessica Lamb. Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
{2}------------------------------------------------
# Indications for Use
510(k) Number (if known) K220956
Device Name Libby™ Echo:Prio
Indications for Use (Describe)
Libby™ Echo:Prio is software that is used to process previously acquired DICOM-compliant cardiac ultrasound images, and to make measurements on these images in order to provide automated estimation of several cardiac measurements.
The data produced by this software is intended to be used to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners for clinical decision-making.
LibbyTM Echo:Prio is indicated for use in adult patients.
| Type of Use (Select one or both, as applicable) | |
|-------------------------------------------------------------------------------|------------------------------------------------------------------------------|
| <div> <span> </span> Prescription Use (Part 21 CFR 801 Subpart D) </div> | <div> <span> </span> Over-The-Counter Use (21 CFR 801 Subpart C) </div> |
# CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
## *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.*
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
> Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
{3}------------------------------------------------
#### 510(k) Summary – Libby™ Echo:Prio 5
#### General Information 5.1
| 510(k) Sponsor | Dyad Medical, Inc |
|-----------------------|---------------------------------------------------------------------------|
| Address | 215 Brighton Avenue, Suite 203<br>Boston, MA 02134 |
| Correspondence Person | Yervant Chijian<br>Quality and Regulatory Consultant<br>Pharmalex Pty Ltd |
| Contact Information | Email: Yervant.Chijian@pharmalex.com<br>Phone: +61 (0)2 9906 2984 |
| Date Prepared | 31st March 2022 |
#### 5.2 Subject Device
| Proprietary Name | Libby™ Echo:Prio |
|---------------------|--------------------------------------------------|
| Common Name | Echo:Prio |
| Classification Name | System, Image Processing, Radiological |
| Regulation Number | 21 CFR 892.2050 |
| Regulation Name | Automated Radiological Image Processing Software |
| Product Code | QIH |
| Regulatory Class | II |
#### 5.3 Predicate Device
| Proprietary Name | EchoMD Automated Ejection Fraction Software |
|------------------------|---------------------------------------------|
| Premarket Notification | K173780 |
| Classification Name | System, Image Processing, Radiological |
| Regulation Number | 21 CFR 892.2050 |
| Regulation Name | Picture archiving and communications system |
| Product Code | LLZ |
| Regulatory Class | II |
#### 5.4 Device Description
Echo:Prio is an image post-processing analysis software device used for viewing and quantifying cardiovascular ultrasound images. The device is intended to aid diagnostic review and analysis of echocardiographic data, patient record management and reporting.
The software provides an interface for a skilled sonographer to perform the necessary markup on the echocardiographic image prior to review by the prescribing physician. The markup includes: the cardiac segments captured, measurements of distance, time, area, quantitative analysis of cardiac function, and a summary report.
{4}------------------------------------------------
Image /page/4/Picture/1 description: The image shows the logo for DYAD Medical. On the left is a blue graphic that looks like three connected water droplets. To the right of the graphic is the text "DYAD" in large, bold, dark blue letters, with the word "MEDICAL" underneath in smaller, lighter blue letters.
The software allows the sonographer to enter their markup manually and/or manually correct automatically generated results. It also provides automated markup and analysis, which the sonographer may choose to accept outright, to accept partially and modify, or to reject and ignore. Machine learning based view classification and border segmentation form the basis for this automated analysis. Additionally, the software has features for organizing, displaying, and comparing to reference guidelines the quantitative data from cardiovascular images acquired from ultrasound scanners.
The following visualization, quantification and data-reporting functionalities are provided by the software:
#### 5.4.1 Visualization:
- . 2D image review
- Cine loop review
- Secondary captures review
#### 5.4.2 Quantification of classification, segmentation and index calculations:
- Echocardiographic View classification
- . End diastole (ED) and End systole (ES) frame identification enabling Heartbeat rate (HR) estimates.
- Ejection fraction (EF)
Notes: This is achieved via automatic left ventricle (LV) chamber endocardium segmentation, left atrium (LA) segmentation, LV myocardium (LVMC) segmentation allowing muscle thickness calculations.
#### 5.4.3 Data reporting
All the above values are reported via a report generation initiated by the investigator.
#### 5.5 Indications for Use
Libby Echo:Prio is software that is used to process previously acquired DICOM-compliant cardiac ultrasound images, and to make measurements on these images in order to provide automated estimation of several cardiac measurements. The data produced by this software is intended to be used to support qualified cardiologists, sonographers, or other licensed professional healthcare practitioners for clinical decision-making.
Libby Echo:Prio is indicated for use in adult patients.
#### ટ.6 Substantial Equivalence
The following table demonstrates the similarities and differences between the technological characteristics of the three products. Testing demonstrates that the differences do not raise new questions of safety or effectiveness.
| Topic | Subject Device<br>Libby™TM Echo:Prio | Predicate Device<br>EchoMD Automated Ejection Fraction<br>Software | Substantial<br>Equivalence |
|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------|
| Intended Use/Indications for<br>Use | Libby™TM Echo:Prio is software that<br>is used to process previously<br>acquired DICOM-compliant | The Bay Labs, Inc. EchoMD<br>Automated Ejection Fraction<br>software is used to process | Same |
| Topic | Subject Device<br>Libby™ Echo:Prio | Predicate Device<br>EchoMD Automated Ejection Fraction<br>Software | Substantial<br>Equivalence |
| | cardiac ultrasound images, and to<br>make measurements on these<br>images in order to provide<br>automated estimation of several<br>cardiac measurements. The data<br>produced by this software is<br>intended to be used to support<br>qualified cardiologists,<br>sonographers, or other licensed<br>professional healthcare<br>practitioners for clinical decision-<br>making.<br>Libby™ Echo:Prio is indicated for<br>use in adult patients. | previously acquired transthoracic<br>cardiac ultrasound images, to store<br>images, and to manipulate and<br>make measurements on images<br>using a personal computer or a<br>compatible DICOM-compliant<br>PACS system in order to provide<br>automated estimation of left<br>ventricular ejection fraction. This<br>measurement can be used to assist<br>the clinician in a cardiac<br>evaluation. The EchoMD<br>Automated EjectionFraction<br>Software is indicatedfor use in<br>adult patients. | |
| Intended User | Cardiologists and sonographers | Cardiologists and sonographers | Same |
| Rx or OTC | Rx | Rx | Same |
| Intended Location | Medical facility | Medical facility | Same |
| High Level Device<br>Description | The Libby™ Echo:Prio is an image<br>post-processing analysis software<br>device used for viewing and<br>quantifying cardiovascular<br>ultrasound images. | EchoMD software is process<br>acquired transthoracic cardiac<br>ultrasound images, to analyze and<br>make measurements on images in<br>order to provide automated<br>estimation of left ventricular<br>ejection fraction | Same |
| Automated Chamber<br>analysis Features & Analysis | Yes | Yes | Same |
| Automated measurements | LV Ejection fraction (EF) | Left ventricular ejection fraction | Same |
| Machine Learning Based<br>Algorithm | Yes | Yes | Same |
| Operate on DICOM clips | Yes | Yes | Same |
| Automated View<br>Classification including:<br>1. long axis view (PLAX)<br>2. short axis view (PSAX)<br>3. four-chamber view (A4C)<br>4. five-chamber view (A5C)<br>5. two-chamber view (A2C)<br>6. long axis view (A3C) | Yes | Yes | Same |
| Automation Level | Fully automated, including clip<br>selection | Fully automated, including clip<br>selection | Same |
| Algorithm Confidence | Qualitative user feedback on<br>transthoracic cardiac<br>ultrasound image quality | Qualitative and quantitative user<br>feedback on transthoracic cardiac<br>ultrasound image quality | Same |
| EF Method | Single plane & biplane (with<br>segmentation and endocardial<br>trace) | Biplane (non-segmentation/ non-<br>endocardial trace) | Same |
| Topic | Subject Device<br>Libby™ Echo:Prio | Predicate Device<br>EchoMD Automated Ejection Fraction<br>Software | Substantial<br>Equivalence |
| Offline EF evaluation using<br>clips from multiple<br>ultrasound scanners | Yes | Yes | Same |
| Automated Ejection Fraction<br>Calculation | Yes | Yes | Same |
| Ejection Fraction reported | Whole number estimate<br>(percentage) | Whole number estimate<br>(percentage) | Same |
| User Confirmation/rejection<br>of result | Yes | Yes | Same |
| Manual editing of<br>automated result by user | Yes | Yes | Same |
| Physical Characteristics | Software package that operates on<br>off-the-shelf hardware | Software package that operates on<br>off-the-shelf hardware | Not equivalent<br>but no issues<br>with safety and<br>efficacy. |
| DICOM Standard Compliance | The software processes DICOM<br>compliant image data | The software processes DICOM<br>compliant image data | Same |
| Modalities | Ultrasound | Ultrasound | Same |
| User Interface | The software is designed for use<br>within a web browser on a personal<br>computer. | The software is designed for use<br>on personal computer or a<br>compatible DICOM-compliant<br>PACS system. | Not equivalent<br>but no issues<br>with safety and<br>efficacy. |
### Table 1: Libby™ Echo:Prio Device Comparison.
{5}------------------------------------------------
Image /page/5/Picture/0 description: The image shows the logo for DYAD MEDICAL. The logo consists of a blue, stylized image of three interconnected circles on the left, and the words "DYAD MEDICAL" in blue on the right. The word "DYAD" is in a larger font than the word "MEDICAL."
{6}------------------------------------------------
Image /page/6/Picture/0 description: The image contains the logo for DYAD Medical. The logo consists of two parts: a blue, abstract, interconnected shape on the left, and the text "DYAD MEDICAL" on the right. The word "DYAD" is in a larger, bolder font, while "MEDICAL" is in a smaller, thinner font.
#### 5.7 Performance Data
Safety and performance of the Libby™ Echo:Prio has been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing. Additionally, the software validation activities were performed in accordance with IEC 62304:2006/AC: 2008- Medical device software – Software life cycle processes, in addition to the FDA Guidance documents, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" and "Content of Premarket Submission for Management of Cybersecurity in Medical Devices."
Performance Testing demonstrated robustness and accuracy retrospectively on a diverse clinical dataset. This demonstrates consistent analysis and low inter/intra-analyst variability of the automated procedures.
The testing demonstrated view classification accuracy of 97% with an average F1 value of >96.6%, average sensitivity (Sn) of 96.8% and average Specificity (Sp) of 98.5%. The testing also demonstrated that the HR output estimate is with minimal bias (slope of 0.98 in linear regression with confidence interval of 95%) compared to the ground truth (12-lead ECG) also showing exceptional accuracy in ED/ES identification.
Finally, the prediction of the EF output using the Libby™ Echo:Prio software had a slope of 0.79 for Bivariate Linear Regression (BLS) with the 95% confidence interval (Cl) of (0.52, 0.98) compared with the annotations by four human experts. This is well within the range of typical measurement variation between different clinicians, which is usually described as inter-observer variation and can be as low as (0.37, 0.52) of the 95% Cl.
{7}------------------------------------------------
Image /page/7/Picture/1 description: The image contains the logo for DYAD MEDICAL. The logo consists of a blue graphic on the left and the text "DYAD MEDICAL" on the right. The graphic appears to be a stylized representation of molecules or cells, with interconnected circles in varying shades of blue. The text "DYAD" is in a bold, dark blue font, while "MEDICAL" is in a thinner, lighter blue font and is positioned below "DYAD".
#### Standards Applied 5.8
The standards applied for the development of the software is listed below:
- NEMA PS 3.1 3.20 2021e Digital Imaging and Communications in Medicine (DICOM) Set .
- . IEC 62304:2006/A1:2016 Medical device software - Software life cycle processes
- ISO 14971:2019 Medical Devices -- Application of Risk Management to Medical Devices ●
- IEC 62366-1 Edition 1.1 2020-06 Medical Devices -- Part 1: Application of Usability Engineering to Medical Devices
- . 21 CFR 820 Quality System Regulations
- ISO 15223-1 Medical devices — Symbols to be used with medical device labels, labelling and information to be supplied — Part 1: General requirements
#### Conclusion 5.9
Based on the information submitted in this premarket notification, and based on the indications for use, technological characteristics and performance testing, the Libby™ Echo:Prio raises no new questions of safety and effectiveness and is substantially equivalent to the predicate device in terms of safety, efficacy, and performance.
{8}------------------------------------------------
Image /page/8/Picture/0 description: The image shows the logo for DYAD Medical. On the left is a blue graphic that looks like three connected water droplets. To the right of the graphic is the text "DYAD" in large, bold, blue letters, with the word "MEDICAL" underneath in smaller, thinner, blue letters.
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.