AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K254255 · Sep 25, 2026
S-Patch CardioAI
Wellysis Corp.
Retrospective 24-hour ambulatory ECG recordings from 496 adult patients
Retrospective clinical performance evaluation of the S-Patch CardioAI algorithm using ECG data collected from five clinical sites to validate beat detection, arrhythmia classification, and signal quality assessment.
496 unique adult patients; Sample Size: 496; Number of Sites: 5
Independent cardiologist-adjudicated annotations
QRS detection, Normal beat classification, SVEB classification, VEB classification, Atrial fibrillation detection, Unreadable interval determination
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
QRS Detection
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
99.9% / 99.4%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Normal Beat Classification
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
100.0% / 99.6%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Supraventricular Ectopic Beat Classification
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
94.6% / 90.2%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Ventricular Ectopic Beat Classification
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
97.3% / 92.5%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Atrial Fibrillation Detection
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
95.4% / 94.7%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Signal Quality Assessment
Deep-learning algorithm combining rule-based logic with AI/ML technology
—
90.7% / 94.6%
—
—
24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites
>1 (cardiologists)
Indications for Use
S-Patch CardioAI is a software application intended for the assessment of cardiac arrhythmias using ambulatory ECG data in adults. It is intended for use by a healthcare solution integrator to build web, mobile, or other types of applications that allow qualified healthcare professionals to review and confirm the analytic results. The product supports downloading and analyzing data recorded in compatible formats from FDA-cleared S-Patch Ex and S-Patch ExL devices when assessment of the rhythm is necessary. S-Patch CardioAI can be electronically interfaced to perform analysis on data transferred from other computer-based ECG systems, such as an ECG management system. S-Patch CardioAI is not intended for use in life-supporting or life-sustaining systems or ECG Alarm devices. The interpretation results generated by S-Patch CardioAI are not intended to be the sole means of diagnosis. Interpretation of the device output must be made by the clinician; the results are offered to physicians and clinicians on an advisory basis only, to be used in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.
Device Story
S-Patch CardioAI is a backend SaMD analysis engine; processes single-lead ECG data from S-Patch Ex/ExL devices or other computer-based ECG systems. Uses a hybrid deep-learning algorithm with rule-based logic to analyze temporal ECG waveforms; detects cardiac beats, classifies arrhythmias, and assesses signal quality. Outputs include QRS, heart rate, RR intervals, heart rate variability, non-paced arrhythmias, ventricular/supraventricular ectopic beats, and signal quality (unreadable) intervals. Accessed via API by third-party software; integrates into web/mobile applications for clinical use in home, clinic, or hospital settings. Operated by healthcare solution integrators; results reviewed by qualified healthcare professionals. Provides advisory information to support clinical decision-making; does not provide automated diagnosis. Benefits include automated, scalable analysis of ambulatory ECG data to assist clinicians in arrhythmia assessment.
Clinical Evidence
Retrospective study of 496 adult patients across five sites (three U.S.). Reference standard: independent cardiologist-adjudicated annotations. Results (Sensitivity/Positive Predictive Value): QRS Detection (99.9%/99.4%), Normal Beat (100.0%/99.6%), SVEB (94.6%/90.2%), VEB (97.3%/92.5%), Atrial Fibrillation (95.4%/94.7%), Unreadable (90.7%/94.6%). All pre-specified acceptance criteria met.
Technological Characteristics
Software-only; web API interface. Complies with ANSI/AAMI/IEC 60601-2-47, AAMI/ANSI/EC57, and ANSI/AAMI/IEC 62304. Hybrid architecture: deep-learning algorithm combined with rule-based logic. Processes single-lead ECG data. Cloud/server-deployable backend engine.
Indications for Use
Indicated for assessment of cardiac arrhythmias using ambulatory ECG data in adults. Not for life-supporting/sustaining systems or ECG alarms. Requires clinician review and confirmation.
Regulatory Classification
Identification
An electrocardiograph is a device used to process the electrical signal transmitted through two or more electrocardiograph electrodes and to produce a visual display of the electrical signal produced by the heart.
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**U.S. FOOD & DRUG**
ADMINISTRATION
September 25, 2026
Wellysis Corp.
Young Juhn
CEO
8f, 425 Teheran-Ro Gangnam--Gu
Seoul, Republic Of Korea
Re: K254255
Trade/Device Name: S-Patch CardioAI
Regulation Number: 21 CFR 870.1425
Regulation Name: Programmable Diagnostic Computer
Regulatory Class: Class II
Product Code: DQK, DPS
Dated: August 24, 2026
Received: August 25, 2026
Dear Young Juhn:
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.
Before making any change significantly affecting the safety or effectiveness of the device, you must submit a new premarket notification in accordance with 21 CFR 807.81. Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K254255 - Young Juhn
Page 2
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 Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13485 clause 8.3 (Nonconforming product), ISO 13485 clause 8.5.2 (Corrective action), and ISO 13485 clause 8.5.3 (Preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 and ISO 13485 clause 7.5) and document changes and approvals in the Medical Device File (ISO 13485 clause 4.2.3).
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 (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-reporting-combination-products); good manufacturing practice requirements as set forth in the Quality Management System Regulation (QMSR) (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-devices/device-advice-comprehensive-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-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/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-devices/device-advice-comprehensive-regulatory-
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K254255 - Young Juhn
Page 3
assistance/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,
KIMBERLY N. CROWLEY - S
For: Jennifer Kozen
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
Please type in the marketing application/submission number, if it is known. This textbox will be left blank for original applications/submissions.
K254255
Please provide the device trade name(s).
S-Patch CardioAI
Please provide your Indications for Use below.
S-Patch CardioAI is a software application intended for the assessment of cardiac arrhythmias using ambulatory ECG data in adults.
It is intended for use by a healthcare solution integrator to build web, mobile, or other types of applications that allow qualified healthcare professionals to review and confirm the analytic results.
The product supports downloading and analyzing data recorded in compatible formats from FDA-cleared S-Patch Ex and S-Patch ExL devices when assessment of the rhythm is necessary.
S-Patch CardioAI can be electronically interfaced to perform analysis on data transferred from other computer-based ECG systems, such as an ECG management system.
S-Patch CardioAI is not intended for use in life-supporting or life-sustaining systems or ECG Alarm devices. The interpretation results generated by S-Patch CardioAI are not intended to be the sole means of diagnosis. Interpretation of the device output must be made by the clinician; the results are offered to physicians and clinicians on an advisory basis only, to be used in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.
CAUTION - Federal (U.S.) law restricts this device to sale by or on the order of a licensed healthcare practitioner.
Please select the types of uses (select one or both, as applicable).
☑ Prescription Use (21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)
?
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Traditional 510(k) Premarket Notification
Wellysis Corp. S-Patch CardioAI
## 510(k) Summary
| **Date Prepared:** | September 24, 2026 |
| --- | --- |
| **Submitter/Applicant:** | Wellysis Corp. 8F, 425, Teheran-ro, Gangnam-gu, Seoul, Republic of Korea |
| **Official Contact:** | Dennis Ahn, Quality Assurance Manager |
| **Primary Contact Person:** | Dennis Ahn Quality Assurance Manager, Wellysis USA Email: dennis.ahn@wellysis.com Phone: (217) 298-6850 |
| **Secondary Contact Person:** | Robert Kazmierski Regulatory Consultant, MCRA. Email: rkazmierski@mcra.com Phone: (443) 831-5064 |
| **Proprietary or Trade Name:** | S-Patch CardioAI |
| **Common/Usual Name:** | Electrocardiograph |
| **Classification Name:** | 21CFR 870.1425 DQK and DPS Class II |
| **Predicate Device:** | DeepRhythmAI, K210822 |
### Device Description:
S-Patch CardioAI is proprietary Software as a Medical Device (SaMD) intended for the automated processing and analysis of single-lead electrocardiogram (ECG) data obtained from S-Patch Ex and S-Patch ExL devices. Operating as a backend analysis engine, it uses a scalable Application Programming Interface (API) to integrate with third-party medical systems that offer visualization and user interface. The product is designed exclusively to provide supportive analytical information to qualified healthcare professionals for review.
The core of S-Patch CardioAI is the deep-learning algorithm that combines rule-based logic with advanced AI/ML technology. This hybrid architecture analyzes the temporal context of ECG waveforms to accurately detect cardiac beats, classify arrhythmias, and assess signal quality.
S-Patch CardioAI can be used to analyze both continuous ECG as well as event recordings. Upon processing, it can generate cardiac classifications and metrics including:
- QRS
- Heart rate determination
- Heart rate variability measurements
K254255 510(k) Summary
Wellysis Corp.
Page 1 / 6
{5}
Traditional 510(k) Premarket Notification
Wellysis Corp. S-Patch CardioAI
- RR Interval measurements
- Non-paced arrhythmias
- Non-paced ventricular arrhythmia calls
- Ventricular ectopic beats
- Supraventricular ectopic beats
- Unreadable (signal-quality) interval determination
S-Patch CardioAI can be deployed as a flexible solution capable of residing within compatible secure computing environments.
### Indications for Use:
S-Patch CardioAI is a software application intended for the assessment of cardiac arrhythmias using ambulatory ECG data in adults.
It is intended for use by a healthcare solution integrator to build web, mobile, or other types of applications that allow qualified healthcare professionals to review and confirm the analytic results.
The product supports downloading and analyzing data recorded in compatible formats from FDA-cleared S-Patch Ex and S-Patch ExL devices when assessment of the rhythm is necessary.
S-Patch CardioAI can be electronically interfaced to perform analysis on data transferred from other computer-based ECG systems, such as an ECG management system.
S-Patch CardioAI is not intended for use in life-supporting or life-sustaining systems or ECG Alarm devices. The interpretation results generated by S-Patch CardioAI are not intended to be the sole means of diagnosis. Interpretation of the device output must be made by the clinician; the results are offered to physicians and clinicians on an advisory basis only, to be used in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information.
CAUTION - Federal (U.S.) law restricts this device to sale, distribution, and use by or on the order of a licensed healthcare practitioner.
### Environments of use:
S-Patch CardioAI is intended for use within secure, controlled computing environments, and its analysis functions are accessed exclusively through its Application Programming Interface (API) by third-party software systems. S-Patch CardioAI supports clinical workflows in home, clinic, and hospital settings through integrated applications that present the analysis results to qualified healthcare professionals. A separate administrative web interface (the Admin Dashboard) is provided for administrators to manage tenants and accounts; it presents no clinical information, supports no clinical task, and is not used for ECG analysis.
Table 3.1. outlines the proposed device vs. the predicate.
As part of the comparison, the following shall be presented & discussed:
- Indications for Use
K254255 510(k) Summary
Wellysis Corp.
Page 2 / 6
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Traditional 510(k) Premarket Notification
Wellyis Corp. S-Patch CardioAI
- Technology and Principle of Operation
Table 3.1 – Comparison – Subject vs. Predicate
| | Predicate DeepRhythmAI | Subject device S-Patch CardioAI | Comments |
| --- | --- | --- | --- |
| K# | K210822 | K254255 | N/A |
| Product Code | DQK and DPS | DQK and DPS | Same |
| Classification | Class II | Class II | Same |
| Regulation Number(s) | 21 CFR §870.1425 21 CFR §870.2340 | 21 CFR §870.1425 21 CFR §870.2340 | Same |
| Classification name | Programmable Diagnostic Computer, Electrocardiograph | Programmable Diagnostic Computer, Electrocardiograph | Same |
| Indications for Use | DeepRhythmAI is a cloud-based software for the assessment of cardiac arrhythmias using two lead ECG data in adult patients. It is intended for use by a healthcare solution integrator to build web, mobile or another types of applications to let qualified healthcare professionals review and confirm the analytic result. The product supports downloading and analyzing data recorded in the compatible formats from dedicated ambulatory ECG devices such as Holter, event recorder, Mobile Cardiac Telemetry or other similar devices when the assessment of the rhythm is necessary. The product can be electronically interfaced and perform analysis with data transferred from other computer-based ECG systems, such as an ECG management system. | S-Patch CardioAI is a software application intended for the assessment of cardiac arrhythmias using ambulatory ECG data in adults. It is intended for use by a healthcare solution integrator to build web, mobile, or other types of applications that allow qualified healthcare professionals to review and confirm the analytic results. The product supports downloading and analyzing data recorded in compatible formats from FDA-cleared S-Patch Ex and S-Patch ExL devices when assessment of the rhythm is necessary. S-Patch CardioAI can be electronically interfaced to perform analysis on data transferred from other computer-based ECG systems, such as an ECG management system. S-Patch CardioAI is not intended for use in life-supporting or life-sustaining | Similar - compatible devices have been evaluated with performance testing |
K254255 510(k) Summary
Wellyis Corp.
Page 3 / 6
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Traditional 510(k) Premarket Notification
Wellysis Corp. S-Patch CardioAI
| | Predicate DeepRhythmAI | Subject device S-Patch CardioAI | Comments |
| --- | --- | --- | --- |
| | DeepRhythmAI can be integrated into medical devices. In this case, the medical device manufacturer will identify the indication for use depending on the application of their device. DeepRhythmAI is not for use in life-supporting or sustaining systems or ECG Alarm devices. Interpretation results are not intended to be the sole means of diagnosis. It is offered to physicians and clinicians on an advisory basis only in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms and other diagnostic information. | systems or ECG Alarm devices. The interpretation results generated by S-Patch CardioAI are not intended to be the sole means of diagnosis. Interpretation of the device output must be made by the clinician; the results are offered to physicians and clinicians on an advisory basis only, to be used in conjunction with the physician's knowledge of ECG patterns, patient background, clinical history, symptoms, and other diagnostic information. CAUTION - Federal (U.S.) law restricts this device to sale, distribution, and use by or on the order of a licensed healthcare practitioner. | |
| Components | Software only: 1) A web API 2) An automated proprietary algorithm. | Software only: 1) A web API 2) An automated proprietary algorithm. | Same |
| Interface | Web application programming interface (API) | Web application programming interface (API) | Same |
| Part responsible for ECG signal analysis | The automated proprietary deep-learning algorithm, which measures and analyzes ECG data to provide qualified healthcare professional with supportive information for review. | The automated proprietary deep-learning algorithm, which measures and analyzes ECG data to provide qualified healthcare professional with supportive information for review. | Same |
| Number of leads for a received ECG signal | Two-lead ECG | Single-lead ECG | Similar – compatible devices have been evaluated with performance testing |
| Display or Graphical User Interface (GUI) | No primary display or GUI | No primary display or GUI | Same |
K254255 510(k) Summary
Wellysis Corp.
Page 4 / 6
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Traditional 510(k) Premarket Notification
Wellysis Corp. S-Patch CardioAI
### Analysis Output Comparison
| Device functionality | S-Patch CardioAI | DeepRhythmAI (K210822)^{1} |
| --- | --- | --- |
| QRS | YES | YES |
| Heart rate determination | YES | YES |
| R-R interval measurement | YES | YES |
| Heart rate variability measurements | YES | Not stated in the cleared 510(k) Summary |
| Non-paced arrhythmia | YES | YES |
| Non-paced ventricular arrhythmia calls | YES | YES |
| Atrial fibrillation detection | YES | YES |
| Ventricular ectopic beats | YES | YES |
| Supraventricular ectopic beats | YES | YES |
| Unreadable (signal-quality) interval determination | YES | Not stated in the cleared 510(k) Summary |
Predicate entries are taken from the cleared K210822 510(k) Summary. "Not stated" indicates that the cleared summary does not describe the item; it is not a statement about the predicate's capability.
The two subject-device outputs not described in the cleared predicate summary — heart-rate-variability indices and the Unreadable (signal-quality) interval determination — are adjunct outputs that were independently validated in the clinical performance testing. They do not alter the intended use or raise no new question of safety or effectiveness compared to the predicate.
### Substantial Equivalence Discussion
S-Patch CardioAI has the same general intended use and similar indications as the predicate device. The subject device's indications for use specify a patient population of adults, consistent with the intended-use population evaluated in performance testing to align with the predicate device's intended-use population. Accordingly, the subject and predicate devices share the same intended-use age range, and this does not constitute a new or different intended use, nor does it raise new questions of safety or effectiveness. The subject device shares the same technological characteristics as the predicate, including compliance with ANSI/AAMI/IEC 60601-2-47, AAMI/ANSI/EC57, and ANSI/AAMI/IEC 62304. A difference in technological characteristics exists in that the subject device uses a single-lead ECG from previously cleared S-Patch devices, as opposed to the predicate's compatibility with two-lead ECGs. This single-lead configuration was validated in the clinical performance testing, and this difference in technological characteristics therefore does not raise new questions of safety or effectiveness.
A further difference exists in the output sets of the two devices: the subject device's core measurement outputs (QRS/heart-rate determination, RR interval measurements, non-paced arrhythmias, non-paced ventricular arrhythmia calls, atrial fibrillation detection, ventricular ectopic beats, and supraventricular ectopic beats) are the same as the predicate's, and it additionally provides heart-rate-variability metrics and the Unreadable (signal-quality) interval determination. These differences do not raise new questions of safety or effectiveness and have been appropriately evaluated to demonstrate the device remains as safe and effective as the predicate device through non-clinical testing according to
K254255 510(k) Summary
Wellysis Corp.
Page 5 / 6
{9}
Traditional 510(k) Premarket Notification
Wellysis Corp. S-Patch CardioAI
AAMI/ANSI/EC57:2012 and clinical performance testing.
## Non-clinical Performance Testing
Non-clinical performance testing was conducted in accordance with ANSI/AAMI EC57:2012/(R)2020 using the standard annotated arrhythmia databases referenced by that standard. Beat detection, beat classification, and ectopic run detection were evaluated.
## Clinical Performance Testing
Clinical performance was evaluated retrospectively using 24-hour S-Patch ECG recordings from 496 unique adult patients across five clinical sites, including three U.S. sites. The validation cohort was independent from model training, tuning, and threshold selection.
Independent cardiologist-adjudicated annotations were used as the clinical reference for beat detection and classification and atrial fibrillation (AF), and an independently adjudicated readability reference was used for the Unreadable output. The table below summarizes the performance of these directly reference-validated outputs. The clinical reference annotations were established through independent cardiologist review and adjudication.
| Output | Clinical Performance (Se/+P) |
| --- | --- |
| QRS Detection | 99.9% / 99.4% |
| Normal Beat (N) Classification | 100.0% / 99.6% |
| SVEB (S) Classification | 94.6% / 90.2% |
| VEB (V) Classification | 97.3% / 92.5% |
| Atrial Fibrillation (episode) | 95.4% / 94.7% |
| Unreadable | 90.7% / 94.6% |
All pre-specified acceptance criteria established for these directly validated outputs were met. Other device outputs were evaluated using validation methods appropriate to each output.
Subgroup analyses across demographic, site/region, rhythm-burden, and recorder-model strata did not identify evident performance degradation in estimable subgroups; low-count strata were descriptively.
## Conclusion
In conclusion, S-Patch CardioAI has the same intended use as the predicate device, and any differences in technological characteristics do not raise different questions of safety or effectiveness. Differences between the subject device and the predicate have been tested to ensure that the device meets its intended use. Therefore, S-Patch CardioAI is substantially equivalent to the predicate device.
K254255 510(k) Summary
Wellysis Corp.
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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.