K241009 · Perigen, Inc. · HGM · Jan 10, 2025 · Obstetrics/Gynecology
Device Facts
Record ID
K241009
Device Name
PeriCALM Patterns 3.0
Applicant
Perigen, Inc.
Product Code
HGM · Obstetrics/Gynecology
Decision Date
Jan 10, 2025
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 884.2740
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Fetal heart rate and uterine contraction pattern annotation
Long and Short-Term Memory (LSTM) neural networks
Inferiority margin of 15% for acceleration/deceleration detection; 10% for baseline level; 95% CI of Bias ≤ 5 bpm
Passed all acceptance criteria
—
—
Retrospective study: 70 subjects (30 preterm, 40 term) with one tracing per subject.
>1 (Obstetrician Gynecologists) + 3 (experts)
Indications for Use
PeriCALM Patterns is intended for use to provide additional secondary information as an adjunct to qualified clinical decision-making during antepartum or intrapartum obstetrical monitoring at ≥32 weeks gestation for annotation and summary of the fetal heart rate recording for baseline, accelerations and decelerations and the uterine pressure recording for contractions. WARNING: Evaluation of FHR during labor and patient management decisions should not be based solely on PeriCALM Patterns annotations or summaries and should include inspection of the fetal monitor tracing and consideration of all pertinent clinical information.
Device Story
Software device for obstetrical care; processes fetal heart rate (FHR) and uterine activity data from external electronic fetal/maternal monitors. Uses Long and Short-Term Memory (LSTM) neural networks to detect, label, and measure FHR features (accelerations, decelerations, baseline) and uterine contractions. Operates in networked or standalone workstation environments. Provides clinicians with summarized measurements in 15 or 30-minute intervals; displays long-term compressed tracing views. Clinicians use output as secondary information to support decision-making; can modify or delete annotations. Benefits include automated pattern recognition and summary to assist in monitoring fetal status during labor or antepartum periods.
Clinical Evidence
Retrospective multi-reader/multi-case study; 70 subjects (30 preterm, 40 term). Compared PeriCALM Patterns 3.0 performance against a panel of 3 expert 'Truthers' and clinician readers. Endpoints included sensitivity, specificity, and PPV for accelerations/decelerations, and Bland-Altman analysis for baseline measurements (bias, LoA). Non-inferiority margins set at 15% for detection and 10% for baseline. Device met all 16 co-primary endpoints, demonstrating non-inferiority to clinician readers across both term and preterm subgroups.
Technological Characteristics
Software-based pattern recognition system. Utilizes signal processing and LSTM neural networks. Inputs: FHR (min 4 samples/sec) and uterine activity (min 1 sample/sec) from external monitors. Connectivity: Networked or standalone workstation. Software evaluated per 2023 FDA guidance for software functions and cybersecurity.
Indications for Use
Indicated for use in pregnant patients at ≥32 weeks gestation during antepartum or intrapartum obstetrical monitoring. Used as an adjunct to clinical decision-making for annotation and summary of fetal heart rate and uterine pressure recordings.
Regulatory Classification
Identification
A perinatal monitoring system is a device used to show graphically the relationship between maternal labor and the fetal heart rate by means of combining and coordinating uterine contraction and fetal heart monitors with appropriate displays of the well-being of the fetus during pregnancy, labor, and delivery. This generic type of device may include any of the devices subject to §§ 884.2600, 884.2640, 884.2660, 884.2675, 884.2700, and 884.2720. This generic type of device may include the following accessories: Central monitoring system and remote repeaters, signal analysis and display equipment, patient and equipment supports, and component parts.
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January 10, 2025
PeriGen, Inc. Candace Alva Director of Regulatory Affairs and Quality Assurance Sderot Nim 2, P.O. Box 110 Rishon LeTziyon, 7510002 Israel
Re: K241009
> Trade/Device Name: PeriCALM Patterns 3.0 Regulation Number: 21 CFR§ 884.2740 Regulation Name: Perinatal Monitoring System and Accessories Regulatory Class: II Product Code: HGM Dated: December 11, 2024 Received: December 11, 2024
Dear Candace Alva:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
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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,
# Monica D. Garcia -S
Monica D. Garcia, Ph.D. Assistant Director DHT3B: Division of Reproductive, Gynecology and Urology Devices OHT3: Office of GastroRenal, ObGyn, General Hospital and Urology Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K241009
Device Name PeriCALM Patterns 3.0
#### Indications for Use (Describe)
PeriCALM Patterns is intended for use to provide additional secondary information as an adjunct to qualified clinical decision-making during antepartum or intrapartum obstetrical monitoring at _32 weeks gestation for annotation and summary of the fetal heart rate recording for baseline, accelerations and the uterine pressure recording for contractions.
WARNING: Evaluation of FHR during labor and patient management decisions should not be based solely on PeriCALM Patterns annotations or summaries and should include inspection of the fetal monitor tracing and consideration of all pertinent clinical information.
| | Type of Use (Select one or both, as applicable) | |
|--|-------------------------------------------------|--|
| | | |
X Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/4/Picture/0 description: The image shows the logo for PeriGen, a company specializing in advanced perinatal systems. The logo features the company name in a teal sans-serif font, with the "P" extending into a partial red circle on the left side. Below the name, in a smaller font, are the words "Advanced Perinatal Systems."
## 510(k) Summary PeriCALM Patterns 3.0 - K241009
| Date Summary Prepared: | January 10, 2025 |
|------------------------------|--------------------------------------------------------------------------------------------|
| Submitter Information | |
| Submitted by: | PeriGen Solutions, Ltd<br>Sderot Nim 2, PO Box 110,<br>Rishon LeTziyon,<br>7510002, Israel |
| Telephone: | +972-3-905-9900 |
| Contact Person: | Natan Blanks<br>GM, Israel Operations |
| Subject Device Information | |
| Device Trade Name: | PeriCALM Patterns 3.0 |
| Common Name: | Computer-based information management system for<br>obstetrical care |
| Regulation Name: | Perinatal monitoring system and accessories |
| Regulation Number | 21 CFR 884.2740 |
| Device Panel: | Obstetrics/Gynecology |
| Product code: | HGM (system, monitoring, perinatal) |
| Regulatory Class: | II |
| Predicate Device Information | |
| Predicate Device: | CALM Patterns PeriGen Solutions, Ltd. (Also listed as<br>PeriCALM Patterns) |
| | The predicate device has not been subject to a design-<br>related recall |
| 510(k) Number | K040788 |
| Device Description | |
PeriCALM Patterns 3.0 is a software device to be used with fetal/maternal monitoring systems. The subject device is a software algorithm to detect, label and measure features (accelerations, decelerations, baseline, and contractions) in electronic fetal monitoring (EFM) records. PeriCALM Patterns 3.0 uses fetal monitor data imported through an interface with an external source or with a third-party clinical information system. PeriCALM Patterns can function in a networked environment or as a standalone workstation.
The subject device includes present-day Long and Short-Term Memory (LSTM) neural networks to identify segments of a fetal heart rate tracing corresponding to accelerations, decelerations, baseline as well as uninterpretable segments where is missing tracing. Contraction detection is achieved using the same processes as the predicate device.
# PeriGen Solutions Ltd.
Azrieli Rishonim | 2 Nim Blvd. POB 110 Rishon LeZion 7510002 Israel
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Image /page/5/Picture/1 description: The image shows the logo for PeriGen, a company that specializes in advanced perinatal systems. The word "PeriGen" is written in a combination of blue and red colors, with the "i" in "PeriGen" being replaced by a red arc. Below the company name, the words "Advanced Perinatal Systems" are written in a smaller, gray font.
#### Indications for Use
PeriCALM Patterns is intended for use to provide additional secondary information as an adjunct to qualified clinical decision-making during antepartum or intrapartum obstetrical monitoring at ≥32 weeks gestation for annotation and summary of the fetal heart rate recording for baseline, accelerations and decelerations and the uterine pressure recording for contractions.
WARNING: Evaluation of FHR during labor and patient management decisions should not be based solely on PeriCALM Patterns annotations or summaries and should include inspection of the fetal monitor tracing and consideration of all pertinent clinical information.
| Comparison of Intended Use and Technological Characteristics of the Subject and Predicate Device | Subject Device<br>PeriGen – PeriCALM Patterns<br>3.0<br>K241009 | Predicate Device<br>PeriGen - PeriCALM<br>Patterns<br>K040788 |
|--------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use | PeriCALM Patterns is intended for<br>use to provide additional<br>secondary information as an<br>adjunct to qualified clinical<br>decision-making during<br>antepartum or intrapartum<br>obstetrical monitoring at ≥32<br>weeks gestation for analysis of the<br>fetal heart rate recording for<br>baseline, accelerations and<br>decelerations and the uterine<br>pressure recording for<br>contractions.<br><br>WARNING: Evaluation of FHR<br>during labor and patient<br>management decisions should not<br>be based solely on PeriCALM<br>Patterns annotations or summaries<br>and should include inspection of<br>the fetal monitor tracing and<br>consideration of all pertinent<br>clinical information. | CALM Patterns is intended for<br>use as an adjunct to qualified<br>clinical decision-making during<br>antepartum or intrapartum<br>obstetrical monitoring at ≥36<br>weeks gestation to obtain<br>annotation of the FHR for<br>baseline, accelerations, and<br>decelerations.<br><br>WARNING: Evaluation of FHR<br>during labor and patient<br>management decisions should not<br>be based solely on CALM<br>Patterns annotations. |
| Applicable gestational age | ≥32 weeks | ≥36 weeks |
| Data Collection | Collects FHR and uterine activity<br>data from electronic<br>maternal/fetal monitors. | Collects FHR and uterine<br>activity data from electronic<br>maternal/fetal monitors. |
| Sample Rate | Samples FHR at a minimum of<br>four samples per second. Samples<br>uterine activity at a minimum or 1<br>sample per second | Samples FHR at a minimum of<br>four samples per second. Samples<br>uterine activity at a minimum or 1<br>sample per second |
## PeriGen Solutions Ltd.
Azrieli Rishonim | 2 Nim Blvd. POB 110 Rishon LeZion 7510002 Israel
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| Pattern recognition module core<br>technology | Signal processing and neural<br>networks | Signal processing and neural<br>networks |
|-----------------------------------------------------------------------------------------------------|------------------------------------------|---------------------------------------------------------|
| Neural network interference:<br>combined accel-decel-baseline<br>+ non-interpretable detection | Yes | No |
| Measurement and labeling<br>accelerations on the tracing | Yes | Yes |
| Baseline measurements | Yes | Yes |
| Contraction measurements | Yes | Yes |
| Analysis provided and<br>summarized in time intervals | 15 or 30 minutes | 20 minutes |
| Provides users with the option to<br>select, modify and export a set of<br>summarized measurements. | Yes | Yes |
| Displays a long-term<br>compressed view of tracing | Yes | Yes |
| Summarizes measurements with<br>the long-term view. | Yes | Yes |
| Handling of disagreements<br>between algorithm detected<br>patterns and clinician opinion | User can delete a feature<br>annotation | User can add, modify or delete a<br>feature annotation. |
| Non-interpretable segments<br>where there is missing tracing | Yes | No |
The indications for use of PeriCALM Patterns 3.0 are similar to the predicate device and the subject and predicate device have the same intended use - as an adjunct to clinical decision making during antepartum, or intrapartum monitoring. The subject device has an extended gestational age from > 32 weeks, compared to the predicate device which has a gestational age from ≥ 36 weeks. This difference in gestational age does not raise different questions of safety and effectiveness.
The technological differences between the subject and predicate device include the addition of neural network interference (combined accel-decel-baseline + non-interpretable detection), different time intervals of analysis, and differences in the managements of non-interpretable segments for a missing trace. These differences do not raise different questions of safety and effectiveness as compared to the predicate device.
## Summary of Non-clinical Performance Testing
#### Software and Cybersecurity
Perinatal Systems
Software was evaluated as recommended in the 2023 FDA guidance document "Content of Premarket Submissions for Device Software Functions." The following activities were successfully completed:
- Risk Analysis / Management
- Requirements Reviews ●
- Design Reviews ●
- Software Verification and Validation
## PeriGen Solutions Ltd.
Azrieli Rishonim | 2 Nim Blvd. POB 110 Rishon LeZion 7510002 Israel
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Image /page/7/Picture/1 description: The image shows the logo for PeriGen. The logo consists of the word "PeriGen" in blue text, with the "P" partially enclosed by a red semi-circle. Below the word "PeriGen" are the words "Advanced Perinatal Systems" in a smaller font size.
The successful V&V tests demonstrate that the device performs in accordance with specifications. Cybersecurity was evaluated as recommended in the 2023 FDA guidance document "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions."
# Summary of Clinical Performance Testing
A retrospective study with multi-reader/multi-case technique was used to determine if the performance of PeriCALM Patterns 3.0 is not inferior to that of a set of qualified and experienced Obstetrician Gynecologists called the Clinician Readers. The predicate device was cleared for use in gestational ages of ≥36 weeks comparing to Ground Truth and Clinician Readers. The same approach was taken for this study, comparing PeriCALM Patterns 3.0 to Ground Truth and Clinician Readers for two gestational age subgroups: ≥36 weeks (term) and 32-35 weeks (pre-term). The ground truth for this study is established by a panel of 3 experts, called the "Truthers". To resolve the inter-observer variation, a majority opinion approach was used. The results of the comparison of the subject device to ground truth is to be non-inferior to the results of the comparison of Readers to ground truth.
A total of 70 subjects (30 preterm and 40 term), with one tracing per subject, were used in the study. Tracings were obtained from hospitals using a variety of fetal monitor models and manufacturers including Corometrics 170, 250 series by GE HealthCare, Avalon FM50 and FM40 by Philips Medical, and S1 from Neoventa and included both antepartum and intrapartum recordings. The tracings were selected from pregnancies with gestational ages from 32 weeks to term, covering a wide range of operating and clinical conditions with respect to maternal BMI, delivery modes, fetal birth weights, hospital types, Apgar scores and antepartum or intrapartum usage.
The study included sixteen (16) co-primary endpoints with different acceptance criteria for noninferiority. Twelve (12) co-primary endpoints pertained to accelerations and decelerations for both gestational groups (i.e., Term and Preterm) and included performance metrics (Sensitivity (Se), Specificity (Sp), Positive Predictive Value (PPV)) of the subject device compared to those of the Readers. Remaining four co-primary endpoints focused on the FHR baseline measurements and were based on Bland-Altman analyses to determine bias, the mean difference between two methods and the Limits of Agreement (LoA) which include 95% of the differences between the two measurement methods. Inferiority margin of 15% for acceleration and deceleration detection and 10% for baseline level was used. The acceptance criteria for 95% CI of Bias for the subject device was set to threshold of ≤ 5 bpm.
PeriCALM Patterns 3.0 passed all acceptance criteria on performance testing regarding pattern detection.
# Conclusion
The performance data described above demonstrate that the PeriCALM Patterns 3.0 is as safe and effective as the PeriCALM Patterns (K040788) and supports a determination of substantial equivalence.
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.