K242919 · V5med, Inc. · OEB · Mar 27, 2025 · Radiology
Device Facts
Record ID
K242919
Device Name
V5med Lung AI
Applicant
V5med, Inc.
Product Code
OEB · Radiology
Decision Date
Mar 27, 2025
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K242919 · Mar 27, 2025
V5med Lung AI
V5med, Inc.
National Lung Screening Trial (NLST) CT dataset
The device performance was validated using a retrospective, multi-reader multi-case (MRMC) study involving 340 chest CT scans sourced from the NLST to assess the impact of the AI on radiologist nodule detection performance.
V5med Lung AI is a Computer-Aided Detection (CAD) software designed to assist radiologists in detecting pulmonary nodules (with diameter of 4-30 mm) during CT examinations of the chest for asymptomatic populations. This software provides adjunctive information to alert radiologists to regions of interest with suspected lung nodules that may otherwise be overlooked. It can be used in a concurrent read mode, where the AI analysis results are displayed alongside the original CT images during either the initial review or any subsequent reviews by the radiologist. V5med Lung AI does not replace the radiologist's critical judgment or diagnostic processes and should not be used in isolation from the original CT series.
Device Story
V5med Lung AI is a CAD software for radiologists; processes chest CT images from PACS, RIS, or scanners. Uses a Deep Convolutional Neural Network (CNN) to automatically detect pulmonary nodules (4-30 mm). Outputs bounding box annotations via DICOM GSPS. Used in clinical settings for concurrent reading; provides adjunctive alerts to assist in identifying nodules that might be overlooked. Does not replace clinical judgment; intended to improve detection accuracy and reduce reading time. Benefits patients through earlier or more reliable nodule identification.
Clinical Evidence
Retrospective, fully crossed, multi-reader multi-case (MRMC) study with 16 radiologists and 340 chest CT scans (screening/non-screening). Primary endpoint: AUC of localization-specific ROC (LROC). Results: Aided AUC 0.830 vs. Unaided 0.734 (difference 0.0959, 95% CI: 0.0586-0.1332). Mean reading time decreased from 133.0s to 115.9s (difference -17.1s, 95% CI: -26.7 to -9.0).
Indicated for asymptomatic patients undergoing chest CT examinations to assist radiologists in detecting pulmonary nodules 4-30 mm in diameter. Not for use in isolation; intended as an adjunctive tool for concurrent reading.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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March 27, 2025
V5med Inc. % Ining Cheng Consultant 7F., No. 36, Chenggong 12th St., Zhubei City Hsinchu County, 302050 TAIWAN
Re: K242919
Trade/Device Name: V5med Lung AI Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: OEB, LLZ Dated: February 24, 2025 Received: February 24, 2025
Dear Ining Cheng:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (the Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
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Additional information about changes that may require a new premarket notification are provided in the FDA
guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
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-regulatory
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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,
Lu Jiang
Lu Jiang, Ph.D. Assistant Director Diagnostic X-Ray Systems Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
Submission Number (if known)
#### K242919
Device Name
V5med Lung Al
#### Indications for Use (Describe)
V5med Lung AI is a Computer-Aided Detection (CAD) software designed to assist radiologists in detecting pulmonary nodules (with diameter of 4-30 mm) during CT examinations of the chest for asymptomatic populations. This software provides adjunctive information to alert radiologists to regions of interest with suspected lung nodules that may otherwise be overlooked. It can be used in a concurrent read mode, where the Al analysis results are displayed alongside the original CT images during either the initial review or any subsequent reviews by the radiologist. V5med Lung Al does not replace the radiologist's critical judgment or diagnostic processes and should not be used in isolation from the original CT series.
Type of Use (Select one or both, as applicable)
> 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/1 description: The image shows the logo for V5med. The logo is in blue and features a stylized "V" and "5" connected together. The "5" has a curved line extending from it, resembling a wave or a swoosh. The word "med" is written in lowercase letters to the right of the "V5" symbol, also in blue.
# 510(k) Summary
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of 21 CFR 807.87(h).
| The assigned 510(k) number is | K242919 |
|----------------------------------------------------|------------------------------------------------|
| Submitter: | V5med Inc. |
| | 7F., No. 36, Chenggong 12th St., Zhubei City, |
| | Hsinchu County, Taiwan |
| | Phone: +886-3-623-3089 |
| Contact Person | JONI CHENG |
| | Email: Joni.Cheng@v5.com.tw |
| | Phone: +886-3-623-3089 |
| Date Prepared | March 26, 2025 |
| Device Name | V5med Lung AI |
| Regulation Name: | Medical image management and processing system |
| CFR Classification: | 21 CFR 892.2050 |
| Device Class | II |
| Product Code: | OEB, LLZ |
| Panel: | Radiology |
| Primary Predicate device: | AVIEW Lung Nodule CAD (K221592) |
| Secondary Predicate device: ClearRead CT (K161201) | |
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Image /page/5/Picture/1 description: The image shows the logo for V5med. The logo is written in a sans-serif font and is blue. The number 5 in the logo has a curved line extending from the bottom of the number. The text "med" is written to the right of the number 5.
## Indications for use
V5med Lung AI is a Computer-Aided Detection (CAD) software designed to assist radiologists in detecting pulmonary nodules (with diameter of 4-30 mm) during chest CT examinations of asymptomatic populations. This software provides adjunctive information to alert radiologists to regions of interest with suspected lung nodules that may otherwise be overlooked. It can be used in a concurrent read mode, where the AI analysis results are displayed alongside the original CT images during either the initial review or any subsequent reviews by the radiologist. V5med Lung AI does not replace the radiologist's clinical judgment or diagnostic processes and should not be used in isolation from the original CT series.
# Device Description
The V5med Lung AI is a software product designed to detect nodules in the lungs. The detection model is trained using a Deep Convolutional Neural Network (CNN) based algorithm, enabling automatic detection of lung nodules ranging from 4 to 30 mm in chest CT images.
The system integrates algorithm logic and database on the same server, ensuring simplicity and ease of maintenance. It accepts chest CT images from a PACS system, Radiological Information System (RIS), or directly from a CT scanner, analyzes the images, and provides output annotations regarding lung nodules.
## Summary of the technological characteristics
V5med Lung AI is functionally equivalent to the following predicate device: AVIEW Lung Nodule CAD (K221592) cleared February 24, 2023.
The following table demonstrates that the intended uses and technical characteristics of V5med Lung AI are substantially equivalent to the predicate devices.
Any differences between the subject device and the predicated device has no negative impact on safety or efficacy of the subject device and does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices.
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Image /page/6/Picture/1 description: The image shows the logo for V5med. The logo is blue and features the text "V5med" in a stylized font. The "V" and "5" are connected, and the "5" has a curved line extending from its bottom, resembling a smile. The word "med" is written in a smaller font size compared to "V5".
# Functional Specification Comparison Table for the V5med Lung AI and AVIEW Lung Nodule CAD (K221592):
| Specification | Subject Device | Primary Predicate Device<br>K221592 | Secondary Predicate Device<br>K161201 | Comparison |
|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device Name | V5med Lung AI | AVIEW Lung Nodule CAD | ClearRead CTTM | N/A |
| Classification Name | Medical Image Management and<br>Processing System | Medical Image Management and<br>Processing System | Medical image management and<br>processing system | Same |
| Device Class | Class II | Class II | Class II | Same |
| Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | Same |
| Product Code | OEB/LLZ | OEB/LLZ | OEB/LLZ | Same |
| Review Panel | Radiology | Radiology | Radiology | Same |
| 510(k) Number | K242919 | K221592 | K161201 | N/A |
| Indications for Use | V5med Lung AI is a Computer-Aided<br>Detection (CAD) software designed to<br>assist radiologists in detecting<br>pulmonary nodules (with diameter of<br>4-30 mm) during CT examinations of<br>the chest for asymptomatic<br>populations. This software provides<br>adjunctive information to alert<br>radiologists to regions of interest with<br>suspected lung nodules that may<br>otherwise be overlooked. It can be<br>used in a concurrent read mode, where<br>the AI analysis results are displayed<br>alongside the original CT images<br>during both the initial review and any<br>subsequent reviews by the radiologist.<br>V5med Lung AI does not replace the<br>radiologist's critical judgment or<br>diagnostic processes and should not<br>be used in isolation from the original<br>CT series. | AVIEW Lung Nodule CAD is a<br>Computer-Aided Detection (CAD)<br>software designed to assist<br>radiologists in the detection of<br>pulmonary nodules (with diameter 3-<br>20 mm) during the review of<br>CT examinations of the chest for<br>asymptomatic populations. AVIEW<br>Lung Nodule CAD provides<br>adjunctive information to alert the<br>radiologists to regions of interest<br>with suspected lung nodules that may<br>otherwise be overlooked. AVIEW<br>Lung Nodule CAD may be used as a<br>second reader after the radiologist<br>has completed their initial read. The<br>algorithm has been validated using<br>non-contrast CT images, the majority<br>of which were acquired on Siemens<br>SOMATOM CT series scanners;<br>therefore, limiting device use to use<br>with Siemens SOMATOM CT series<br>is recommended. | ClearRead CTTM is comprised of<br>computer assisted reading tools<br>designed to aid the radiologist in the<br>detection of pulmonary nodules<br>during review of CT examinations of<br>the chest on an asymptomatic<br>population. The ClearRead CT<br>requires both lungs be in the field of<br>view. ClearRead CT provides<br>adjunctive information and is not<br>intended to be used without the<br>original CT series. | V5med Lung AI and AVIEW Lung<br>Nodule CAD (predicate device) are<br>both Computer-Aided Detection (CAD)<br>software designed to assist radiologists<br>in detecting pulmonary nodules during<br>CT examinations of the chest for<br>asymptomatic populations. Both<br>provide adjunctive information to alert<br>radiologists to regions of interest with<br>suspected lung nodules that may<br>otherwise be overlooked.<br>However, V5med Lung AI supports a<br>broader nodule diameter range (4-30<br>mm), compared to AVIEW's range of<br>3-20 mm, making it similar to<br>ClearRead CTTM, which also covers<br>nodules from 5-20 mm. Additionally,<br>V5med Lung AI does not restrict the<br>use to non-contrast images, unlike<br>AVIEW, aligning it more closely with<br>ClearRead CTTM. Furthermore, V5med<br>Lung AI does not limit the scanner<br>source, while AVIEW is validated |
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Image /page/7/Picture/1 description: The image shows the logo for V5med. The logo is in blue and features a stylized "V" and "5" connected together. The word "med" is written in lowercase letters to the right of the "V5".
| General Description | | | | |
|------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | The V5med Lung AI is a software product designed to detect nodules in the lungs. The detection model is trained using a Deep Convolutional Neural Network (CNN) based algorithm, enabling automatic detection of lung nodules ranging from 4 to 30 mm in chest CT images. The system integrates algorithm logic and database on the same server, ensuring simplicity and ease of maintenance. It accepts chest CT images from a Picture Archiving and Communication System (PACS), Radiological Information System (RIS), or directly from a CT scanner, analyzes the images, and provides output annotations regarding lung nodules. | The AVIEW Lung Nodule CAD is a software product that detects nodules in the lung. The lung nodule detection model was trained by Deep Convolution Neural Network (CNN) based algorithm from the chest CT image. Automatic detection of lung nodules of 3 to 20mm in chest CT images. By complying with DICOM standards, this product can be linked with the Picture Archiving and Communication System (PACS) and provides a separate user interface to provide functions such as analyzing, identifying, storing, and transmitting quantified values related to lung nodules. The CAD's results could be displayed after the user's first read, and the user could select or de-select the mark provided by the CAD. The device's performance was validated with SIEMENS' SOMATOM series manufacturing. The device is intended to be used with a cleared AVIEW platform. | ClearRead CT is a dedicated post-processing application that generates a secondary vessel suppressed Lung CT series with CADe marks and associated region descriptors intended to aid the radiologist in the detection of pulmonary nodules. | primarily with Siemens SOMATOM CT series scanners, making V5med Lung AI more flexible like ClearRead CTTM. These differences do not impact the safety and effectiveness of V5med Lung AI.<br>V5med Lung AI and AVIEW Lung Nodule CAD both utilize Deep Convolutional Neural Network (CNN) based algorithms for lung nodule detection in chest CT images. However V5med Lung AI supports a broader nodule detection range of 4 to 30 mm, compared to AVIEW's 3 to 20 mm, making it similar to ClearRead CT™™, which also covers nodules from 5 - 20 mm. Unlike AVIEW, which is validated with SIEMENS' SOMATOM series and intended to be used with a cleared AVIEW platform, V5med Lung AI does not restrict the scanner source or the use of non-contrast images, aligning it more closely with ClearReac CT™™ in terms of flexibility. These differences do not impact the safety and effectiveness of V5med Lung AI. |
| Detection target(s) | Pulmonary nodules in screening and diagnostic chest CT acquisitions. | Pulmonary nodules in non-contrast chest CT acquisitions | Pulmonary nodules in chest CT acquisitions. | The detection targets of V5med Lung AI are similar to the detection targets of the predicate devices. |
| Nodule Characteristics | Diameter: | Diameter: | Diameter: | Diameter: |
| | • Pulmonary nodules 4 – 30 mm | • Pulmonary nodules 3 – 20 mm | • Pulmonary nodules 5 – 20 mm | The diameter range of V5med<br>Lung AI is similar to the<br>predicate devices |
| | Locations:<br>• Full range: central, peripheral | Locations:<br>• Full range: central, peripheral<br>Contours:<br>• Round, irregular | | Locations:<br>• Same as primary predicate |
| Nodule Marking | A bounding box is provided around<br>nodules | A bounding box is provided around<br>nodules | A bounding box is provided around<br>nodules | Same |
| Automatically locate<br>and identify lung<br>nodules | Yes | Yes | Yes | Same |
| Modifies the Original<br>CT scan | No | No | Yes | Same as AVIEW Lung Nodule CAD. |
| Image format | DICOM | DICOM | DICOM | Same |
| Hosting Platform | - | AVIEW | - | No specific hosting platform. Same as<br>cleared ClearRead CT. |
| Hosting Application | - | AVIEW LCS | - | No specific hosting application. Same<br>as cleared ClearRead CT. |
| Outputs | DICOM GSPS (Grayscale Softcopy<br>Presentation State) | DICOM GSPS (Grayscale Softcopy<br>Presentation State)<br>XML (Coordinate of detected<br>nodules)<br>Able to view results<br>on AVIEW, AVIEW<br>LCS viewer page | DICOM GSPS (Grayscale Softcopy<br>Presentation State) | Similar to AVIEW Lung Nodule CAD<br>but lacks XML output and specific<br>viewer capabilities of AVIEW.<br>The outputs of V5med Lung AI are<br>similar to the outputs of the predicate<br>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.