Retrospective clinical data from trauma registries and medical records were used to validate the performance of the APPRAISE-HRI algorithm in identifying hemorrhage risk in adult trauma patients.
Clinical utility study; Retrospective validation of algorithm using prospectively collected vital-sign data
Adult trauma patients (age ≥18 and ≤90 years); Sample Size: 5,895 patients; Number of Sites: 9 (8 transport sites, 1 emergency department)
Control patients (defined by trauma registry data/clinical documentation)
Likelihood Ratios for HRI Levels I, II, and III
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Hemorrhage risk stratification
AI linear regression model
—
Likelihood Ratio for Level I: 0.18; Level II: 0.70; Level III: 6.88
—
—
Clinical utility study: 5,895 trauma patients across eight transport sites and one hospital Emergency Department.
—
Indications for Use
The APPRAISE-HRI is a mobile health app intended to provide a means for military healthcare providers to screen U.S. Service members for hemorrhage risk after a physically traumatic event and stratify casualties who need immediate attention and emergency evacuation from those who are injured but may not be at risk for hemorrhage. The APPRAISE-HRI is not intended to diagnose or direct treatment. Rather, it is intended to provide situational awareness and inform clinical management of potentially hemorrhagic casualties by identifying those at the greatest risk of hemorrhage.
Device Story
Android mobile app; receives real-time HR, SBP, and DBP data via Bluetooth from ZOLL Propaq M monitor. Algorithm processes vital signs to generate hemorrhage risk score every minute. Displays risk level (I, II, or III) to military healthcare providers (medics) to provide situational awareness. Assists in clinical management and triage decisions for trauma casualties. Benefits include improved identification of patients at high risk of hemorrhage, facilitating timely evacuation and intervention.
Clinical Evidence
Prospective-retrospective clinical utility study (n=5,895) evaluated performance using trauma registry data. Primary endpoint: Likelihood Ratios (LR) for HRI levels. Results: HRI Level I LR 0.18 (95% CI 0.12-0.26); HRI Level II LR 0.70 (95% CI 0.63-0.76); HRI Level III LR 6.88 (95% CI 6.04-7.84). Demonstrated effective differentiation of hemorrhage risk across age, injury mode, and study sites.
Technological Characteristics
Android application (v9-13); Bluetooth connectivity to external monitor (ZOLL Propaq M). Inputs: HR, SBP, DBP. Output: Hemorrhage Risk Index (Levels I-III). Software lifecycle per IEC 62304; risk management per ISO 14971. Algorithm: AI-based linear regression model.
Indications for Use
Indicated for U.S. Service members (adults 18-90 years) following a physically traumatic event to screen for hemorrhage risk and stratify casualties requiring immediate attention/evacuation versus those at lower risk.
Regulatory Classification
Identification
An adjunctive hemodynamic indicator with decision point is a device that identifies and monitors hemodynamic condition(s) of interest and provides notifications at a clinically meaningful decision point. This device is intended to be used adjunctively along with other monitoring and patient information.
Special Controls
In combination with the general controls of the FD&C Act, the adjunctive hemodynamic indicator with decision point is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) Software description, verification, and validation based on comprehensive hazard analysis and risk assessment must be provided, including:
(i) Full characterization of technical parameters of the software, including algorithm(s);
(ii) Description of the expected impact of all applicable sensor acquisition hardware characteristics on performance and any associated hardware specifications;
(iii) Specification of acceptable incoming sensor data quality control measures;
(iv) Mitigation of impact of user error or failure of any subsystem components (signal detection and analysis, data display, and storage) on output accuracy; and
(v) The sensitivity, specificity, positive predictive value, and negative predictive value in both percentage and number form for clinically meaningful pre-specified time windows consistent with the device output.
(2) Scientific justification for the validity of the hemodynamic indicator algorithm(s) must be provided. Verification of algorithm calculations and validation testing of the algorithm must use an independent data set.
(3) Usability assessment must be provided to demonstrate that risk of misinterpretation of the status indicator is appropriately mitigated.
(4) Clinical data must support the intended use and include the following:
(i) The assessment must include a summary of the clinical data used, including source, patient demographics, and any techniques used for annotating and separating the data;
(ii) Output measure(s) must be compared to an acceptable reference method to demonstrate that the output represents the measure(s) that the device provides in an accurate and reproducible manner;
(iii) The data set must be representative of the intended use population for the device. Any selection criteria or limitations of the samples must be fully described and justified;
(iv) Where continuous measurement variables are displayed, agreement of the output with the reference measure(s) must be assessed across the full measurement range; and
(v) Data must be provided within the clinical validation study or using equivalent datasets to demonstrate the consistency of the output and be representative of the range of data sources and data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment.
(5) Labeling must include the following:
(i) The type of sensor data used, including specification of compatible sensors for data acquisition, and a clear description of what the device measures and outputs to the user;
(ii) Warnings identifying factors that may impact output results;
(iii) Guidance for interpretation of the outputs, including warning(s) specifying adjunctive use of the measurements;
(iv) Key assumptions made in the calculation and determination of measurements; and
(v) A summary of the clinical validation data, including details of the patient population studied (
*e.g.,* age, gender, race/ethnicity), clinical study protocols, and device performance with confidence intervals for all intended use populations.
Predicate Devices
Analytic for Hemodynamic Instability (AHI) (DEN200022)
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA text logo on the right. The FDA text logo is in blue and includes the letters "FDA" followed by "U.S. FOOD & DRUG ADMINISTRATION" in a smaller font size.
April 5, 2024
The Surgeon General, Department of the Army (TSG-DA) % Chandar Thakur Acting Branch Chief, Medical Devices & Diagnostics, Office of Regulatory Activities U.S. Army Medical Materiel Research & Development Command; Attn: Fcmr-ora, 1430 Veterans Drive Fort Detrick, Maryland 21702
Re: K233249
Trade/Device Name: APPRAISE-HRI Regulation Number: 21 CFR 870.2220 Regulation Name: Adjunctive Hemodynamic Indicator With Decision Point Regulatory Class: Class II Product Code: SAR Dated: February 27, 2024 Received: February 27, 2024
Dear Chandar Thakur:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device"
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(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 OS 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.
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,
# Stephen C. Browning -S
LCDR Stephen Browning Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular 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) K233249
Device Name APPRAISE-HRI
#### Indications for Use (Describe)
The APPRAISE-HRI is a mobile health app intended to provide a means for military healthcare providers to screen U.S. Service members for hemorrhage risk after a physically traumatic event and stratify casualties who need immediate attention and emergency evacuation from those who are injured but may not be at risk for hemorrhage.
The APPRAISE-HRI is not intended to diagnose or direct treatment. Rather, it is intended to provide situational awareness and inform clinical management of potentially hemorrhagic casualties by identifying those at the greatest risk of hemorrhage.
| Type of Use (Select one or both, as applicable) | |
|----------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
| <div> <span> Prescription Use (Part 21 CFR 801 Subpart D) </span> </div> | <div> <span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> </div> |
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# ATTACHMENT 18.1 A4 510(k) SUMMARY
### Contact Details
#### Applicant Details:
The Surgeon General, Department of the Army (TSG-DA), Ms. Emily Badraslioglu, U.S. Army Medical Research & Development Command; ATTN: FCMR-ORA, 1430 Veterans Drive, Fort Detrick, MD 21702-5009, United States Phone: 301-619-0317 Email: emily.d.badraslioglu.civ(@health.mil
#### Correspondent Details:
Dr. Chandar Thakur, U.S. Army Medical Research & Development Command; ATTN: FCMR-ORA 1430 Veterans Drive, Fort Detrick MD 21702-5009 United States Phone: 301-619-0317 Email: chandar.s.thakur.civ(@health.mil
Date Prepared: March 27, 2024
#### Subject Device Details
| Device Trade Name: | APPRAISE-HRI |
|----------------------------|--------------------------------------------------------------------------|
| Common Name: | Adjunctive Hemorrhage Risk Indicator |
| Classification: | Class II |
| Classification Regulation: | 21.CFR.870.2220: Adjunctive Hemodynamic Indicator with Decision<br>Point |
| Product Code: | SAR |
#### Predicate Device Details
| Device Trade Name: | Analytic for Hemodynamic Instability (AHI) |
|----------------------------|--------------------------------------------------------------------------|
| De Novo number: | DEN200022 |
| Common Name: | Adjunctive Hemodynamic Indicator with Decision Point |
| Classification: | Class II |
| Classification Regulation: | 21.CFR.870.2220: Adjunctive Hemodynamic Indicator with Decision<br>Point |
| Product Code: | QNV |
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# Device Description
The Automated Processing of the Physiological Registry for Assessment of Injury Severity (APPRAISE)-Hemorrhage Risk Index (HRI) is an Android application developed by the U.S. Army Medical Research and Development Command (USAMRDC) that uses vital-sign data collected from a trauma patient to provide a risk score that stratifies the patient's risk of hemorrhage. When the application runs, heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) vital-sign data are collected from an external monitor [currently only the ZOLL Propaq M (K202375) is supported]. The ZOLL Propaq M monitor connects via Bluetooth with the Android platform running the APPRAISE-HRI application. The APPRAISE-HRI application continuously pulls data from the ZOLL Propaq M monitor to gather the required vital signs (HR, SBP, and DBP) and then runs the hemorrhage risk stratification algorithm to generate an output every one minute.
Once the vital-sign data from the ZOLL Propaq M monitor are transferred, the APPRAISE-HRI provides a stratification of hemorrhage into three Risk Level categories: Low (I), Average (II), or High (II). The APPRAISE-HRI application continuously displays both the input vital signs (HR, SBP, and DBP) and the Risk Level score to the caregiver to provide situational awareness and to inform clinical management of potentially hemorrhagic casualties by identifying those at the greatest risk of hemorrhage.
# Indications for Use Statement
The APPRAISE-HRI is a mobile health app intended to provide a means for military healthcare providers to screen U.S. Service members for hemorrhage risk after a physically traumatic event and stratify casualties who need immediate attention and emergency evacuation from those who are injured but may not be at risk for hemorrhage.
The APPRAISE-HRI is not intended to diagnose or direct treatment. Rather, it is intended to provide situational awareness and inform clinical management of potentially hemorrhagic casualties by identifying those at the greatest risk of hemorrhage.
# Software Functionality
APPRAISE-HRI is an application designed to run on the Android platform. It targets Android 13, but it is compatible with Android versions 9 through 13, excluding Android 12L. The application is designed to be device agnostic, supporting devices with touch screens that have resolution of at least 1200x800 dp. APPRAISE-HRI does not require any other hardware features except for Bluetooth. The software of the application is divided by function into three major components: graphical user interface, services, and the APPRAISE-HRI algorithm.
The graphical user interface (GUI) consists of three pages: the MainActivity Page, the PreferenceActivity Page, and the WebViewActivity Page. They provide functionality to control the device settings and display results of the APPRAISE-HRI algorithm. The services component of APPRAISE-HRI mobile app allows the application to communicate with the ZOLL Propaq M monitor, request and receive real-time data, and feed real-time data to the APPRAISE-HRI algorithm.
The APPRAISE-HRI algorithm, which provides the core functionality to this device, consists of three modules. The first module pre-processes the raw vital-sign data and provides minute-byminute values as valid input for the second module, an artificial intelligence (AI) linear regression model. Then, the third module stratifies the output of the AI model to yield three
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hemorrhage risk indices: HRI Levels I, II, or III. An HRI Level of I indicates that the likelihood of the patient experiencing hemorrhage is highly decreased compared to the population average; an HRI Level of II indicates that the likelihood of hemorrhage is equivalent to that of a trauma population: and an HRI Level of III indicates that the likelihood of the patient experiencing hemorrhage is highly increased compared to the population average.
# Summary of Performance Testing
### Software Verification Tests
Non-clinical software tests (Unit, Integration, and System levels) were conducted for the subject device, APPRAISE-HRI, during product development. The risk analysis was completed, and risk controls were implemented to mitigate identified hazards. The test results support that all the software specifications have met the acceptance criteria. The subject device, APPRAISE-HRI, conforms to the following voluntary standards: 1) "ISO 14971:2019 - Medical devices application of risk management to medical devices" and 2) "IEC 62304 2016 – Medical device software - software life cycle processes."
The level of software documentation for the subject device. APPRAISE-HRI, was determined to be "Enhanced Documentation Level," according to the risk analysis and rationale set forth in the June 14, 2023, FDA Guidance for the Content of Premarket Submissions for Device Software Functions.
# Summative Usability Testing (Usability Study)
USAMRDC conducted a summative study as part of the usability assessment evaluation of the subject device, APPRAISE-HRI. The summative study was conducted to ensure that the device user interface has been designed so that user error is reduced or eliminated and that it meets the intended users' (i.e., Army medics') needs.
The responses of the participating Army medics on the summative study based on the Likert-scale questionnaire show that the medics found it easy to determine a patient's hemorrhage risk using APPRAISE-HRI. In addition, they agreed that using the APPRAISE-HRI app will help to identify patients with a risk of hemorrhage. The medics also responded that the instructions for use of the APPRAISE-HRI were easy to follow. Further, the study provided evidence that participants were able to correctly interpret the device output.
Intended users (i.e., Army medics) are expected to receive training on the use and interpretation of the device prior to first use.
# Clinical Study Validation
A clinical utility study was conducted to evaluate the performance of the APPRAISE-HRI in realworld trauma patients. This "prospectively, retrospectively" design study prospectively validated the APPRAISE-HRI device using retrospectively collected vital-sign data both during transport of trauma patients from the point of injury to the receiving hospital (eight sites) and at a hospital's Emergency Department (one site). The targeted population for the APPRAISE-HRI is adult trauma patients (patient age range is ≥18 and ≤90 years) who were labeled as Hemorrhage patients or Control patients based on trauma registry data, including blood transfusion information and documented hemorrhagic injuries, such as clinical notes, International Classification of Disease 10th Revision (ICD-10) codes, and Abbreviated Injury Scale (AIS) codes.
The primary endpoint used to validate the APPRAISE-HRI was the Likelihood Ratios for HRI
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Levels I, II, and III, for the first HRI output of each patient. The secondary endpoints included other statistical metrics, analysis of different subgroups of interest [age, mode of injury (blunt vs. penetrating), and clinical study site], and analysis through time. The success criteria for the APPRAISE-HRI device required that it effectively and consistently differentiated between HRI Levels, I, II, and III and that the ground truth for trauma patients tracked consistently with the algorithm results.
As shown in Table 1, the primary endpoint results demonstrate that the key test statistics, the Likelihood Ratios of the APPRAISE-HRI Levels, met the success criteria: APPRAISE-HRI was at least five times less likely to output an HRI Level I for Hemorrhage patients than for Control patients; APPRAISE-HRI was almost as likely to output an HRI Level II for Hemorrhage patients as for Control patients; and APPRAISE-HRI was nearly seven times more likely to output an HRI Level III for Hemorrhage patients than for Control patients. These results indicate that the APPRAISE-HRI is a useful tool to aid in discriminating hemorrhage risk in the trauma population.
| Test Level | # of Hemorrhage<br>Patients | # of Control<br>Patients | Total # of<br>Patients | Likelihood Ratio<br>[95% CI*] |
|---------------|-----------------------------|--------------------------|------------------------|-------------------------------|
| HRI Level I | 25 | 1,347 | 1,372 | 0.18 [0.12, 0.26] |
| HRI Level II | 257 | 3,631 | 3,888 | 0.70 [0.63, 0.76] |
| HRI Level III | 261 | 374 | 635 | 6.88 [6.04, 7.84] |
| Total | 543 | 5,352 | 5,895 | |
Table 1: APPRAISE-HRI Algorithm for the Detection or Exclusion of Hemorrhage.
* Confidence intervals (CI) computed based on 10,000 samples with replacement from the dataset.
The APPRAISE-HRI performed consistently across subgroups (age categories, modes of injury, and study sites), with the exception of ruling in hemorrhage patients with penetrating injury (mainly due to low numbers of the patient population recorded with penetrating injury). Based on the clinical results, the APPRAISE-HRI met the Special Control (b) (4) of 21CFR870.2220.
# Conclusion (Substantial Equivalence Discussion)
The subject device, APPRAISE-HRI, and its predicate (DEN200022) have the same intended use and similar indication for use, similar technological characteristics, and, overall, similar principles of operation. There is a minor difference between the subject device, the APPRAISE-HRI, and the predicate's (DEN200022) indications for use (the subject device is indicated for hemorrhage condition and the predicate is indicated for hemodynamic condition). In addition, they are used both in different patient populations and use environments. However, these differences do not constitute a new indication for use, because both the subject device and the predicate device are intended to be used adjunctively to monitor blood (hemo-) related conditions along with other cardiovascular monitoring devices.
The other minor differences between the subject device and the predicate are certain technological characteristics and principles of operation (such as different algorithm inputs and outputs). However, these differences do not raise additional safety and efficacy questions because the safety and performance of the subject device, the APPRAISE-HRI, were evaluated as per the verification and validation testing.
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Therefore, the noted differences do not raise different questions of safety or effectiveness, and the results of software verification, usability testing, and clinical validation demonstrate that the subject device performs in accordance with specifications and meets user needs. The subject device, APPRAISE-HRI, has been demonstrated to be substantially equivalent to the identified predicate device (DEN200022).
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1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
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Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
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Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
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Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
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Reading rule for every project: how many summaries do you read in full?
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Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
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Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
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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.
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Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.