The TM eCloud ECG Analysis System, using proprietary algorithm, is intended for use in adults and children of any age from birth upwards. The Program makes significant use of the patient's age and gender and will provide a unique diagnosis if age differs only by a few days in the case of neonates. It is a program that is based on normal limits derived using the algorithm itself with this applying to criteria for subjects of all ages, including neonates. TM eCloud ECG Analysis System is qualified to evaluate, detect, and aid in the physician diagnosis of the following cardiac arrhythmias and/or conduction defects: Evaluation of symptoms that may be caused by cardiac arrhythmia and /or conduction disturbances Evaluation of symptoms that may be due to myocardial ischemia Detection of ECG events that alter prognosis in certain forms of heart disease Detection and analysis of indirect pacemaker function and failure Determination of cardiac response to lifestyle Evaluation of therapeutic interventions Investigations in epidemiology and clinical trials Evaluation of heart rate variability in the assessment of heart disease TM eCloud ECG Analysis System is intended to provide an interpretation of up to 12-channel ECG in all situations including resting and ambulatory ECG including Holter, cardiac event, and mobile cardiac telemetry. This software qualifies to be used in hospitals, physician offices, and scanning services. It is designed for acquisition, analysis, edit, review, report and storage of all ECG and multi-parameter data. It is capable of diagnosing all commonly recognized ECG abnormalities such as myocardial infarction (MI), acute MI, ventricular hypertrophy, abnormal ST-T changes, lethal arrhythmias, and common rhythm abnormalities. TM eCloud ECG Analysis System can analyze recordings performed on newborns, children, and adults. TM eCloud ECG Analysis System's interpretation results are not intended to be the sole means of diagnosis for any abnormal ECG that may be detected. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG.
Device Story
System comprises cloud-based PaaS, desktop client, and physician portal. Inputs: 1-12 channel ECG data (10 seconds to 60 days) from various stationary/ambulatory devices; proprietary adapters convert data to Physionet WFDB format. Processing: proprietary 12-lead or reduced-lead analysis engines detect arrhythmias (ectopy, pauses, heart block, etc.), ST anomalies, and QT prolongation. Output: diagnostic reports, ECG visualizations (5-min to daily views), and HRV metrics. Used by technicians and physicians in clinical settings. Workflow: data upload via cellular/web; automated analysis; technician review/edit; physician final sign-off. Benefits: assists clinicians in identifying cardiac abnormalities and monitoring therapeutic interventions; provides advisory interpretation to support clinical decision-making.
Clinical Evidence
Bench testing only. Performance validated using standardized databases: CSE, Glasgow (Adult, Pediatric, Pacemaker, AF), MIT-BIH Arrhythmia, AHA Ventricular Arrhythmia, Noise Stress Test, Congestive Heart Failure RR Interval, Creighton University Ventricular Tachyarrhythmia, and European ST-T databases. Testing confirmed accuracy of QRS detection, heart rate measurement, VEB detection, ventricular flutter/fibrillation, supraventricular ectopic beats, and ST segment deviation detection per ANSI/AAMI EC57:2012.
Technological Characteristics
Cloud-based PaaS architecture with desktop client and web portal. Supports 1-12 channel ECG analysis. Data format: Physionet WFDB. Connectivity: cellular, REST web service, FTP. Software-based analysis engine. Complies with ANSI/AAMI EC57:2012 for rhythm and ST segment measurement.
Indications for Use
Indicated for adults and children (including neonates) to evaluate, detect, and aid in physician diagnosis of cardiac arrhythmias, conduction defects, myocardial ischemia, and heart rate variability. Used for resting and ambulatory ECG (Holter, event, mobile telemetry) in hospitals, offices, and scanning services.
Regulatory Classification
Identification
A programmable diagnostic computer is a device that can be programmed to compute various physiologic or blood flow parameters based on the output from one or more electrodes, transducers, or measuring devices; this device includes any associated commercially supplied programs.
Predicate Devices
GE Healthcare MARS Holter Analysis Workstation (K132437)
Agilent Technologies 2010 Plus Holter for Windows (K003940)
Medtronic, Inc. Paceart Optima System Software (K110693)
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Public Health Service
Image /page/0/Picture/2 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo is a circular emblem with the words "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" arranged around the perimeter. Inside the circle is a stylized image of three human profiles facing to the right, with flowing lines representing hair or fabric.
Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002
September 21, 2015
Telemed Solutions, Inc. Ken Burns CEO 6251 Schaefer Avenue, Suite K Chino, California 91710
Re: K142349
Trade/Device Name: TM eCloud ECG Analysis System Regulation Number: 21 CFR 870.1425 Regulation Name: Programmable Diagnostic Computer Regulatory Class: Class II Product Code: DOK, KRE, MLO, DPS, DXH, OUG Dated: August 11, 2015 Received: August 13, 2015
Dear Ken Burns.
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. 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
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Part 807); labeling (21 CFR Part 801); medical device reporting of medical devicerelated adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. 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
http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
M.A. Hillebrand
for
Bram D. Zuckerman, M.D. Director Division of Cardiovascular Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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# Indications for Use
## Device Name: TM eCloud ECG Analysis System
#### 1. Indications for Use:
The TM eCloud ECG Analysis System, using proprietary algorithm, is intended for use in adults and children of any age from birth upwards. The Program makes significant use of the patient's age and gender and will provide a unique diagnosis if age differs only by a few days in the case of neonates. It is a program that is based on normal limits derived using the algorithm itself with this applying to criteria for subjects of all ages, including neonates.
TM eCloud ECG Analysis System is qualified to evaluate, detect, and aid in the physician diagnosis of the following cardiac arrhythmias and/or conduction defects:
- o Evaluation of symptoms that may be caused by cardiac arrhythmia and /or conduction disturbances
- Evaluation of symptoms that may be due to myocardial ischemia
- Detection of ECG events that alter prognosis in certain forms of heart disease
- Detection and analysis of indirect pacemaker function and failure
- Determination of cardiac response to lifestyle
- Evaluation of therapeutic interventions
- . Investigations in epidemiology and clinical trials
- Evaluation of heart rate variability in the assessment of heart disease
TM eCloud ECG Analysis System is intended to provide an interpretation of up to 12-channel ECG in all situations including resting and ambulatory ECG including Holter, cardiac event, and mobile cardiac telemetry. This software qualifies to be used in hospitals, physician offices, and scanning services. It is designed for acquisition, analysis, edit, review, report and storage of all ECG and multi-parameter data. It is capable of diagnosing all commonly recognized ECG abnormalities such as myocardial infarction (MI), acute MI, ventricular hypertrophy, abnormal ST-T changes, lethal arrhythmias, and common rhythm abnormalities.
TM eCloud ECG Analysis System can analyze recordings performed on newborns, children, and adults.
TM eCloud ECG Analysis System's interpretation results are not intended to be the sole means of diagnosis for any abnormal ECG that may be detected. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG.
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Prescription Use _____________________________________________________________________________________________________________________________________________________________ (Part 21 CFR 801 Subpart D) and/or
Over-The-Counter Use_ (21 CFR 801 Subpart C)
(Please Do Not Write Below This Line)
Concurrence of CDRH, Office of Device Evaluation (ODE)
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# 5-1 510(k) Summary of Safety and Effectiveness
#### 1. General Information
#### Submitter:
| Company | Telemed Solutions Inc. |
|----------------|-----------------------------------------------|
| Address | 6251 Schaefer Ave, Suite K<br>Chino, CA 91710 |
| Contact: | Ken Burns |
| Telephone: | (909) 628-8787 |
| Date Prepared: | March 5, 2015 |
#### Device:
| Trade Name: | TM eCloud ECG Analysis System |
|----------------------|-----------------------------------------------------------------|
| Common Name: | ECG Analysis Software (per 21 CFR 870.1425) |
| Classification Name: | Programmable Diagnostic Computer |
| Product Code: | DQK, KRE, MLO, DPS, DXH, OUG |
| Regulation: | 21 CFR 870.1425, 870.36, 870.2800, 870.2340, 870.2920, 880.6310 |
| Class: | II |
### 2. Predicated Devices:
The legally marketed predicated devices to which equivalence is being claimed is:
| GE Healthcare. | MARS Holter Analysis Workstation | K132437 |
|----------------------|----------------------------------|---------|
| Agilent Technologies | 2010 Plus Holter for Windows | K003940 |
| Medtronic, Inc. | Paceart Optima™ System Software | K110693 |
| Memtec Corporation | MobileECG | K103427 |
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#### 3. Device Description:
The TM eCloud ECG Analysis System consists of a (1) server-side, application Platform as a Service (PaaS) cloud based system, a (2) desktop client-side application, and (3) a web-based Physician Portal website.
The (1) server-side, application PaaS component collects, stores, performs arrhythmia analysis on ECG uploads, and transfers data to and from the client-side application.
The (2) desktop client-side application is a workstation system which allows technicians to review ECG, edit the analysis results produced by the (1) server-side, application PaaS component, and generate reports for the ECG study. The edited results and reports are uploaded to the (1) server-side, application PaaS component. It also allows notifications and updates to (3) Physician Portal website.
The TM eCloud ECG Analysis System is capable of processing and performing arrhythmia analysis on ten seconds to 60 days of recorded ECG from one to 12 channels. The system is designed to be compatible with any stationary or ambulatory ECG device having the ability to export ECG. Typical compatible devices interfaces include Cardiac Mobile Telemetry, Event recorders, and Holter recorders but is not limited to a particular ECG device. ECG interfaces from desperate devices are translated by Telemed Adapters which convert proprietary formats to the Physionet WFDB MIT format but vendors may choose to provide the Physionet WFDB directly and bypass the use of an adapter.
The purpose of the TM eCloud ECG Analysis System is to determine if any irregular rhythms, irregular beats, conduction defects, or ST depression occurred during the recording or monitoring. A qualified physician can then use the results of the analysis report to determine what action needs to be taken to help the patient reduce or prevent the occurrence of these abnormalities.
The users may upload ECG to the TM eCloud ECG Analysis System via a cellular network, REST web service, or FTP from any computer or cellular equipment. The system performs analysis on the uploaded ECG using the proprietary 12 Lead Diagnostic EKG Analysis Engine or proprietary algorithm Reduced Lead 1-7 lead Analysis Engine and downloads the results to the client.
If detected, the ECG engine will report on the following arrhythmias: ventricular ectopy, atrial ectopy, pauses, heart block, junctional rhythms, hemiblock, LBBB, RBBB, ST anomalies, and prolonged QT. It will display up to 900 statements including atrial fibrillation, ventricular fibrillation/flutter, and WPW.
The (2) client workstation software employs several screens to display the ECG data. These screens include: 5-Minute View, Hourly view, or Daily view, 8-Second View, Arrhythmias Only View, time and frequency domain HRV, ST changes, AF burden. All analyzed data is saved in a database. From there data can be organized into a report that can be printed on paper or distributed electronically.
Although the analysis engine reports arrhythmias and abnormalities with a high rate of accuracy, all results need to be reviewed and/or edited by a qualified medical professional.
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#### 4. Indications for Use:
The TM eCloud ECG Analysis System, using a proprietary algorithm, is intended for use in adults and children of any age from birth upwards. The Program makes significant use of the patient's age and gender and will provide a unique diagnosis if age differs only by a few days in the case of neonates. It is a program that is based on normal limits derived using the algorithm itself with this applying to criteria for subjects of all ages, including neonates.
The TM eCloud ECG Analysis System is qualified to evaluate, detect, and aid in the physician diagnosis of the following cardiac arrhythmias and/or conduction defects:
- . Evaluation of symptoms that may be caused by cardiac arrhythmia and /or conduction disturbances
- Evaluation of symptoms that may be due to myocardial ischemia
- Detection of ECG events that alter prognosis in certain forms of heart disease
- Detection and analysis of indirect pacemaker function and failure
- Determination of cardiac response to lifestyle
- Evaluation of therapeutic interventions
- Investigations in epidemiology and clinical trials
- Evaluation of heart rate variability in the assessment of heart disease
The TM eCloud ECG Analysis System is intended to provide an interpretation of up to 12-channel ECG in all situations including resting and ambulatory ECG including Holter, cardiac event, and mobile cardiac telemetry. This software qualifies to be used in hospitals, physician offices, and scanning services. It is designed for acquisition, analysis, edit, review, report and storage of all ECG and multiparameter data. It is capable of diagnosing all commonly recognized ECG abnormalities such as myocardial infarction (MI), acute MI, ventricular hypertrophy, abnormal ST-T changes, lethal arrhythmias, and common rhythm abnormalities.
The TM eCloud ECG Analysis System can analyze recordings performed on newborns, children, and adults.
The TM eCloud ECG Analysis System's interpretation results are not intended to be the sole means of diagnosis for any abnormal ECG that may be detected. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG.
#### 5. Non-clinical Tests Used in Determination of Substantial Equivalence:
Non-clinical tests were performed to compare TM eCloud ECG Analysis System to the predicated devices.
The following applicable standards were used to compare the TM eCloud ECG Analysis System to the predicate devices:
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ANSI/AAMI EC57:2012 - Testing and reporting performance results of cardiac rhythm and ST segment measurement algorithms.
#### 6. Databases used for Non-Clinical Testing:
- CSE (Common Standards for Quantitative Electrocardiography) Database The CSE database consisted of 1220 ECGs recorded from individuals living in several European countries
- Glasgow 1000 ECG Database The 1000 ECG database was selected to provide a wide range of normal and abnormal ECGs, including arrhythmias, conduction defects, etc.
- Glasgow Adult Normal Database The normal ECG database was composed of ECGs recorded from 1498 apparently healthy individuals who were each examined by a physician and who had no evidence of heart disease or any other condition such as diabetes which might be expected to lead to cardiovascular abnormalities. This database has been used extensively in the determination of normal limits of ECGs such as those relating to the QT interval
- Glasgow Pediatric ECG Database This database of 840 ECGs was recorded from neonates, infants and children referred or admitted to hospital for investigation of various problems.
- Glasgow Pacemaker ECG Database This database was composed of 47 ECGs were selected where the pacemaker stimuli were seen to be correctly detected from inspection of relevant indicators on the ECG printout.
- Glasgow Atrial Fibrillation Database In order to supplement the number of cases of atrial fibrillation, an additional 72 cases were added to the database of 1000 ECGs from which rhythm analysis was assessed.
#### Reduced lead testing was performed in accordance with ANSI/AAMI EC57/Ed.3, Testing and reporting performance results of cardiac rhythm and ST segment measurement algorithms:
- . Accuracy of QRS detection analysis was tested using the MIT-BIH Arrhythmia Database, AHA Database of Evaluation of Ventricular Arrhythmia Detectors, and Noise Stress Test Database.
- Accuracy of heart rate measurements (HRV) was tested using the MIT-BIH Arrhythmia Database, AHA Database of Evaluation of Ventricular Arrhythmia Detectors, Noise Stress Test Database, and Congestive Heart Failure RR Interval Database.
- Accuracy of VEB detection analysis was tested using the MIT-BIH Arrhythmia Database, AHA ● Database of Evaluation of Ventricular Arrhythmia Detectors, and Noise Stress Test Database
- Accuracy of Ventricular Flutter or Fibrillations was tested using the MIT-BIH Arrhythmia Database, AHA Database of Evaluation of Ventricular Arrhythmia Detectors, and Creighton University Ventricular Tachyarrhythmia Database (CU)
- Accuracy of supraventricular ectopic beats and Atrial Flutter or Fibrillations was tested using the MIT-BIH Arrhythmia Database and Noise Stress Test Database
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- Accuracy of ST segment deviations or to detect ST changes was tested using the European ST-. T Database
# 7. Conclusions from Non-clinical Testing
After comparing predicated devices to Telemed Solutions' TM eCloud ECG Analysis System, results show that with the intended use, the software is equivalent in safety and effectiveness. Therefore Telemed Solutions supports a claim: TM eCloud ECG Analysis System is substantially equivalent to the predicate devices.
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.