The AITRICS-VC is stand-alone software intended to analyze patient data sourced from an EHR (Electronic Health Record) system and display data of in-hospital patients. It displays patient data whose vital signs, blood test results, or conventional early warning scores such as MEWS, NEWS, and qSOFA exceed predefined thresholds. It is not intended to replace bedside patient monitors or clinicians' clinical decision-making. It is not indicated for use in high-acuity environments like the ICU or operating rooms for acutely or critically ill patients. It may be used by clinicians to aid in understanding a patient's current condition and changes over time. The AITRICS-VC is solely indicated for use in the general ward of a hospital environment.
Device Story
AITRICS-VC is stand-alone clinical decision support software; inputs patient physiological data (vital signs, blood test results) from hospital EHR via HL7 feed. Device performs rule-based calculations for conventional early warning scores (NEWS, MEWS, qSOFA). System screens patients against predefined thresholds; displays multi-patient dashboard and individual patient details via web browser on clinician PCs. Used by clinicians in general hospital wards to aid understanding of patient condition and longitudinal changes. Does not replace bedside monitors or clinical judgment; intended to assist in timely, informed decision-making. Benefits include improved visibility of patient status and potential for earlier clinical intervention.
Clinical Evidence
No clinical data. Bench testing only; demonstrated compliance with IEC 62304, IEC 62366-1, and IEC 60601-1-8.
Technological Characteristics
Stand-alone software; web-based interface. Connectivity via HL7 feed from EHR. Rule-based algorithm for early warning score calculation (NEWS, MEWS, qSOFA). Compliant with IEC 62304 (software lifecycle), IEC 62366-1 (usability), and IEC 60601-1-8 (alarm systems).
Indications for Use
Indicated for in-hospital patients in general wards. Used by clinicians to monitor vital signs, blood test results, and early warning scores (MEWS, NEWS, qSOFA) exceeding predefined thresholds. Contraindicated for use in high-acuity environments like the ICU or operating rooms for acutely or critically ill patients.
Regulatory Classification
Identification
A cardiac monitor (including cardiotachometer and rate alarm) is a device used to measure the heart rate from an analog signal produced by an electrocardiograph, vectorcardiograph, or blood pressure monitor. This device may sound an alarm when the heart rate falls outside preset upper and lower limits.
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July 23, 2024
AITRICS Co.,Ltd. Dongyeop Kim RA/QA manager 13F, 218, Teheran-ro, Gangnam-gu Seoul. 06221 Korea, South
Re: K240756
Trade/Device Name: AITRICS-VC Regulation Number: 21 CFR 870.2300 Regulation Name: Cardiac Monitor (Including Cardiotachometer And Rate Alarm) Regulatory Class: Class II Product Code: PLB Dated: March 18, 2024 Received: March 20, 2024
Dear Dongyeop Kim:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (OS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
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.
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,
for
Robert T. Kazmierski -S
LCDR Stephen Browning Assistant Director DHT2A: Division of Cardiac Electrophysiology, Diagnostics
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and Monitoring Devices OHT2: 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) K240756
Device Name AITRICS-VC
#### Indications for Use (Describe)
The AITRICS-VC is stand-alone software intended to analyze patient data sourced from an EHR (Electronic Health Record) system and display data of in-hospital patient data whose vital signs, blood test results, or conventional early warning scores such as MEWS, and qSOFA exceed predefined thresholds. It is not intended to replace bedside patient monitors or clinical decision-making. It is not indicated for use in high-acuity environments like the ICU or operating rooms for acutely or critically ill patients. It may be used by clinicians to aid in understanding a patient's current condition and changes over time. The AITRICS-VC is solely indicated for use in the general ward of a hospital environment.
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------|
|-------------------------------------------------|
X Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
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Image /page/4/Picture/0 description: The image shows the logo for AI TRICS. The logo is green and features the letters "AI" inside of a rounded square. To the right of the square are the letters "TRICS".
# 510(k) Summary
This summary of safety and effectiveness information is prepared in accordance with the requirements of 21 CFR 807.92.
Date Prepared: March 20, 2024
## l. Submitter
Applicant: AITRICS Co.,Ltd. 13F, 218, Teheran-ro, Gangnam-gu, Seoul, Republic of Korea (06221) Phone: +82 2 569 5507
Contact Person: Dongyeop Kim RA/QA Manager
Prepared by: Dongyeop Kim, RA/QA Manager Sojeong Kim, RA manager Sangjun Lee, RA Manager Sun Young Kim, RA Manager
## II. Device
Device Name: AITRICS-VC Common Name: Cardiac monitor (including cardiotachometer and rate alarm) Classification Name: Multivariate Vital Signs Index Regulation Number: 870.2300 Product Code: PLB
## III. Predicate Device
510(k) No.: K213335 Device Name: Capsule Surveillance System Product Code: MWI
# IV. Device Description
AITRICS-VC is a clinical decision support software that receives in-hospital patient information, including physiological parameters such as vital signs and blood test results from EHR and conducts rule-based calculations for conventional early warning scores, which include NEWS (National Early Warning Score), MEWS (Modified Early Warning Score), and qSOFA (quickSOFA).
The AITRICS-VC screens patients who meet predefined criteria based on single values of physiological parameters and early warning scores. It displays a multi-patient dashboard and detailed pages for individual patients via a web browser on clinicians' PCs.
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# V. Intended Use / Indications for Use
The AITRICS-VC is stand-alone software intended to analyze patient data sourced from an EHR (Electronic Health Record) system and display data of in-hospital patients. It displays patient data whose vital signs, blood test results, or conventional early warning scores such as MEWS, NEWS, and qSOFA exceed predefined thresholds. It is not intended to replace bedside patient monitors or clinicians' clinical decision-making. It is not indicated for use in high-acuity environments like the ICU or operating rooms for acutely or critically ill patients. It may be used by clinicians to aid in understanding a patient's current condition and changes over time. The AITRICS-VC is solely indicated for use in the general ward of a hospital environment.
## [Comparison of Intended Use with Predicate Device]
Operational and technological characteristics for the determination of substantial equivalence of the subject device with the predicate device. The difference of technological characteristics does not raise new questions of safety and effectiveness and both devices have same intended use.
# VI. Comparison of Technology Characteristics
The subject device and the predicate device are substantially equivalent in most technical characteristics. Both devices are used by clinicians and are utilized for analyzing and displaying patient data from EHR system in hospital settings. While there is a different technical characteristic for the output, the output of the subject device aligns with methods commonly used by clinicians, being encompassed by the methods of the predicate device, which are described as "clinical practices, protocols, and policies." Therefore, this difference raises no new questions of safety and effectiveness.
| Attribute | Subject Device (AITRICS-VC) | Predicate Device |
|----------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Product<br>Code | PLB: Multivariate Vital Signs Index | MWI: Physiological Patient Monitor<br>(without arrhythmia detection or<br>alarms) |
| Indications<br>for Use | The AITRICS-VC is stand-alone<br>software intended to analyze patient<br>data sourced from an EHR (Electronic<br>Health Record) system and display<br>data of in-hospital patients.<br>It displays patient data whose vital<br>signs, blood test results, or<br>conventional early warning scores<br>such as MEWS, NEWS, and qSOFA<br>exceed predefined thresholds.<br>It is not intended to replace bedside<br>patient monitors or clinicians' clinical | The Capsule Surveillance is a clinical<br>decision support device that<br>integrates, analyzes, and displays data<br>from multiple sources including<br>medical devices and healthcare<br>information systems.<br>It uses standardized rules that are<br>based on customers approved clinical<br>practices, protocols, and policies to<br>create clinically relevant alerts in<br>health care facilities when used by<br>clinical physicians or appropriate |
| Attribute | Subject Device (AITRICS-VC) | Predicate Device |
| | decision-making.<br>It is not indicated for use in high-<br>acuity environments like the ICU or<br>operating rooms for acutely or<br>critically ill patients.<br>It may be used by clinicians to aid in<br>understanding a patient's current<br>condition and changes over time.<br>The AITRICS-VC is solely indicated for<br>use in the general ward of a hospital<br>environment. | medical staff under the direction of<br>physicians.<br>It is not intended to replace clinicians'<br>judgment, but rather to assist<br>clinicians in making timely, informed,<br>higher quality decisions.<br>Capsule Surveillance may be<br>configured for secondary monitoring<br>and alerting intended to be relied<br>upon in deciding to take immediate<br>clinical action.<br>Capsule Surveillance may also be<br>configured for remote display of<br>physiological data and alerts not<br>intended to be relied upon in deciding<br>to take immediate clinical action. |
| Intended<br>User | Clinicians | Clinicians |
| Target<br>Patients/<br>Environment<br>of Use | Patients at general ward in hospital<br>setting | Patients in hospital setting |
| Application<br>Type | Remote display via a web browser | Two types; The workstation used<br>exclusively in kiosk mode and the<br>remote display via a web browser |
| Application<br>Views | Two types; multi-patient<br>simultaneous monitoring and detailed<br>views/monitoring of single patients | Two types; multi-patient<br>simultaneous monitoring and detailed<br>views/monitoring of single patients |
| Data Input | EHR system via HL7 feed | EHR systems as well as medical<br>devices via HL7 feed |
| Output | Patient information is displayed when<br>patient data whose vital signs, blood<br>test results, or conventional early<br>warning scores exceed predefined<br>thresholds. | Clinically relevant alerts are created<br>by standardized rules that are based<br>on customers approved clinical<br>practices, protocols, and policies. |
| Performance<br>data | Tests according to harmonized<br>standards below.<br>IEC 62304:2006/A1:2016<br>IEC 62366- 1:2015+AMDI:2020<br>IEC 60601-1-8 | Tests according to harmonized<br>standards below.<br>IEC 62304:2006/A1:2016<br>IEC 62366- 1:2015+AMDI:2020<br>IEC 60601-1-8 |
| Clinical data | Not require clinical data | Not require clinical data |
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# VII. Performance Data
The AITRICS-VC has passed all non-clinical tests for demonstrated compliance with the harmonized standards below.
- . IEC 62304 Ed 1.1 2015-06 | Medical device software – Software life cycle processes
- IEC 62366-1 Ed 1.1 2020-06 | Medical devices – Part 1 Application of usability engineering to medical devices
- . IEC 60601-1-8 Ed 2.2 2020-07 | Medical electrical equipment - Part 1-8: General requirements for basic safety and essential performance - Collateral Standard: General requirements, tests and guidance for alarm systems in medical electrical equipment and medical electrical systems
No new issues of safety or effectiveness are introduced as a result of using this device.
This device does not require clinical data.
# VIII. Conclusions
The results of the substantial equivalence discussion including non-clinical tests demonstrate that the AITRICS-VC does not raise new questions of safety and effectiveness, performs as intended are substantially equivalent to the predicate device.
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Part 1 — Search, results, and everyday workflows 16 min
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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?
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.
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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.
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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.
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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.
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.