Prospective, multicenter, nonrandomized, repository study (N=1,816).
—
Indications for Use
The CorVista® System analyzes sensor-acquired physiological signals of patients presenting with cardiovascular symptoms (such as chest pain, dyspnea, fatigue) to indicate the likelihood of significant coronary artery disease. The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.
Device Story
CorVista System is a non-invasive, modular diagnostic platform; acquires physiological signals via 7-channel VCG (cardiac electrical) and PPG (hemodynamic) sensors; processes data through a machine-learning detection algorithm to output a likelihood score for significant coronary artery disease (CAD). Used in professional healthcare settings (clinics, hospitals) by clinicians; output displayed on tablet, mobile, or web portal. Assists healthcare providers in clinical decision-making by providing diagnostic aid for symptomatic patients; intended to be used alongside clinical judgment, patient history, and physical signs. Benefits include non-invasive assessment of CAD likelihood, potentially streamlining diagnostic pathways.
Clinical Evidence
Prospective, multicenter, nonrandomized study (N=1,816) of symptomatic patients. Ground truth established via invasive coronary angiography (ICA) or Computed Tomography Angiography (CTA). Performance metrics: 88% sensitivity, 51% specificity, 0.80 AUC-ROC. Repeatability and reproducibility confirmed via IDENTIFY study (multiple signals collected by same/different coordinators).
Technological Characteristics
Modular system: CorVista Base System (hardware/firmware/software) + CAD Add-On Module. Sensors: 7-channel VCG lead set, PPG sensor. Connectivity: Cellular/WiFi to web-based portal. Standards: IEC 60601-1, 60601-1-2, 60601-2-25, 80601-2-61, 60259, 62133, AIM 7351731, ANSI IEEE C63.27, FCC Part 15. Biocompatibility: ISO 10993-1, 10993-5, 10993-10. Algorithm: Machine learning-based detection.
Indications for Use
Indicated for adult patients presenting with cardiovascular symptoms (e.g., chest pain, dyspnea, fatigue) to aid in the diagnosis of significant coronary artery disease (CAD).
Regulatory Classification
Identification
Viz HCM is a cardiovascular machine learning-based notification software intended to be used in parallel to the standard of care to analyze 12-lead ECG recordings from patients 18 years of age or older. It detects signs associated with hypertrophic cardiomyopathy (HCM) and allows the user to view the ECG and analysis results. It is not intended for use on patients with implanted pacemakers, does not replace standard diagnostic methods, and is not intended to rule out HCM or be used in lieu of a full patient evaluation.
Special Controls
In combination with the general controls of the FD&C Act, cardiovascular machine learningbased notification software is subject to the following special controls:
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September 8, 2023
CorVista Health, Inc. Gabrielle Zaeska Vice President Regulatory Affairs 7144 13th Place NW. Suite 2200 Washington, District of Columbia 20012
Re: K232686
Trade/Device Name: CorVista® System Regulation Number: 21 CFR 870.2380 Regulation Name: Cardiovascular machine learning-based notification software Regulatory Class: Class II Product Code: QXX, DQK Dated: September 1, 2023 Received: September 1, 2023
Dear Gabrielle Zaeska:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. 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 located 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.
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
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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 803) for devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-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/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
# Stephen G. Browning -S
LCDR Stephen Browning Assistant Director Division of Cardiac Electrophysiology, Diagnostics and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K232686
Device Name CorVista® System
#### Indications for Use (Describe)
The CorVista® System analyzes sensor-acquired physiological signals of patients presenting with cardiovascular symptoms (such as chest pain, dyspnea, fatigue) to indicate the likelihood of significant coronary artery disease. The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.
Type of Use (Select one or both, as applicable)
| <span style="font-size:12pt;">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) | <span style="font-size:12pt;">☐</span> Over-The-Counter Use (21 CFR 801 Subpart C) |
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## Summary of 510(k)
## CorVista Health, Inc. [510(k) Number - K232686]
This 510(k) Summary is in conformance with 21 CFR 807.92
| Submitter: | CorVista Health, Inc. (“CorVista Health”)<br>7144 13th Place NW, Suite 200<br>Washington, DC 20012<br>Phone: 919-619-7581<br>Fax: 919-573-9105 |
|-----------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Primary Contact: | Gabrielle Zaeska<br>Vice President, Regulatory Affairs & Quality<br>CorVista Health, Inc.<br>Email: gzaeska@corvista.com<br>Phone: 612-267-5004<br>Fax: 919-573-9105 |
| Alternate Contact: | Tom McDougal<br>Principal Regulatory Affairs Specialist<br>CorVista Health, Inc.<br>Email: tmcdougal@corvista.com<br>Phone: 919-813-2724 ext 1058<br>Fax: 919-573-9105 |
| Date Prepared: | 1 September 2023 |
| Trade Name: | CorVista® System |
| Common Name: | Cardiovascular machine learning-based notification software |
| Classification: | Class II |
| Regulation Number: | 21 CFR 870.2380 |
| Classification Panel: | Cardiovascular |
| Product Code: | QXX |
Subsequent Product Code: DQK
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| | Predicate |
|---------------------------|-----------------|
| Trade / Device Name | Viz HCM |
| 510(k) Submitter / Holder | Viz.ai, Inc. |
| 510(k) Number | DEN230003 |
| Regulation Number | 21 CFR 870.2380 |
| Classification Panel | Cardiovascular |
| Product Code | OXO |
The predicate device has not been subject to a design-related recall.
#### Device Description
The CorVista® System is a non-invasive medical device system comprised of several hardware and software components that are designed to work together to allow a physician to evaluate the patient for the presence of cardiac disease, or cardiac disease indicators, using a static detection algorithm.
The CorVista System has a modular design, where disease-specific "Add-On Modules" will integrate with a single platform, the CorVista Base System, to realize its intended use. The CorVista Base System is a combination of hardware, firmware, and software components with the functionality to acquire, transmit, store, and analyze data, and to generate a report for display in a secure web-based portal. The architecture of the CorVista Base system allows for integration with indication-specific "Add-Ons" which perform data analysis using a machine learned detection algorithm to indicate the likelihood of specific diseases at point of care. The CAD Add-On indicates the likelihood of significant Coronary Artery Disease (CAD). The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.
#### Indications for Use
The Cor Vista® System analyzes sensor-acquired physiological signals of patients presenting with cardiovascular symptoms (such as chest pain, dyspnea, fatigue) to indicate the likelihood of significant coronary artery disease. The analysis is presented for interpretation by healthcare providers in conjunction with their clinical judgment, the patient's signs, symptoms, and clinical history as an aid in diagnosis.
### Substantial Equivalence
The CorVista System is substantially equivalent to its predicate device, Viz HCM (DEN230003).
The table below provides a detailed comparison of the CorVista System to the predicate device.
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| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
|------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use | The CorVista® System is<br>intended to non-invasively<br>analyze physiological signals<br>using machine learning<br>techniques to indicate the<br>likelihood of a cardiovascular<br>disease or condition | Viz HCM is intended to non-<br>invasively analyze physiological<br>signals using machine learning<br>techniques to suggest the<br>likelihood of a cardiovascular<br>disease or condition | Same |
| Indications for Use | The CorVista® System<br>analyzes sensor-acquired<br>physiological signals of patients<br>presenting with cardiovascular<br>symptoms (such as chest pain,<br>dyspnea, fatigue) to indicate the<br>likelihood of<br>significant coronary artery<br>disease. The analysis is<br>presented for interpretation by<br>healthcare providers in<br>conjunction with their clinical<br>judgment, the patient's signs,<br>symptoms, and clinical history<br>as an aid in diagnosis. | Viz HCM is intended to be used in<br>parallel to the standard of care to<br>analyze recordings of 12-lead<br>ECG made on compatible ECG<br>devices. Viz HCM is capable of<br>analyzing the ECG, detecting signs<br>associated with hypertrophic<br>cardiomyopathy (HCM), and<br>allowing the user to view the ECG<br>and analysis results. Viz HCM is<br>indicated for use on 12-lead ECG<br>recordings collected from patients<br>18 years of age or older. Viz HCM<br>is not intended for use on patients<br>with implanted pacemakers.<br><br>Viz HCM is limited to analysis of<br>ECG data and should not be used<br>in-lieu of full patient evaluation or<br>relied upon to make or confirm<br>diagnosis. Viz HCM identifies<br>patients for further HCM follow-<br>up and does not replace the current | Different - This difference does<br>not change the intended use of the<br>device. The safety and<br>effectiveness of the CorVista<br>System in its intended use<br>population has been confirmed<br>through testing.<br><br>Any differences in the indications<br>for use do not affect the safety and<br>effectiveness of the CorVista<br>System and have been addressed<br>through clinical and bench testing<br>and supported by general and<br>special controls. |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Product Codes | (primary) QXX<br>(21 CFR 870.2380)<br><br>(subsequent product code)<br>DQK<br>(21 CFR 870.1425) | standard of care methods for<br>diagnosis of HCM. The results of<br>the device are not intended to rule-<br>out HCM follow-up.<br><br>(primary predicate) QXO<br>(21 CFR 870.2380)<br><br>(reference predicates)<br>DQK<br>(21 CFR 870.1425) | Different – codes reflect the<br>disease state detected and<br>hardware components. This<br>difference does not change the<br>intended use of the device |
| Operation Mode | Spot-check | Viz HCM (DEN230003) | Same |
| Motion | Non-motion | Spot-check<br>HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate ClarisTM System v1.2<br>(K210392)<br>Both secondary predicates are<br>intended for non-motion. | Same |
| Patient Population | Adult patients presenting with<br>cardiovascular symptoms | Viz HCM (DEN230003)<br>Adult patients | Different - This difference does<br>not change the intended use of the<br>device. The safety and<br>effectiveness of the CorVista<br>System in its intended use<br>population has been confirmed<br>through testing |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Environment of Use | Professional healthcare<br>environment (i.e., local<br>physician offices, clinics and<br>hospital settings) with cellular<br>or Wifi | Viz HCM (DEN230003)<br>Hospital and pre-hospital settings | Same |
| Prescription vs. Off-<br>the-Shelf | Prescription | Viz HCM (DEN230003)<br>Prescription | Same |
| Technological Characteristics | | | |
| Algorithm | Machine learning-based<br>algorithm | Viz HCM (DEN230003)<br>Machine learning-based algorithm | Same |
| Algorithm Calculation<br>and Output | Likelihood of significant CAD<br>derived from calculated VCG<br>and PPG features and patient<br>demographics. | Viz HCM (DEN230003)<br>Presence of signs of HCM derived<br>from ECG signal. | Different – The output of the<br>CorVista System provides users<br>with the likelihood of significant<br>CAD for a given patient. The<br>primary predicate indicates the<br>presence of signs of HCM. These<br>signs are equivalent in concept to<br>the calculated features that are<br>used as the inputs to the CorVista<br>machine-learning process and<br>resultant algorithm. Both devices<br>process signals to provide<br>information to users on<br>cardiovascular disease and as such<br>the intended use is not impacted<br>by this difference. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Ground Truth for<br>Model Training and<br>Validation | Guideline-driven ground truth<br>via invasive catheterization or<br>core-lab adjudicated CTA | Viz HCM (DEN230003)<br>Cardiologist-adjudicated signs of a<br>disease from ECG waveform | Different – The validation of the<br>two devices differs in the level of<br>ground truth that is used to<br>validate performance. The<br>CorVista System has been<br>validated using the patient's<br>disease state as ground truth, while<br>the predicate device utilizes the<br>presence of signs that suggest<br>disease. This difference does not<br>impact the shared general intended<br>use of providing information on<br>cardiovascular status. The safety<br>and effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Measured<br>Physiological<br>Parameters | Synchronously acquired cardiac<br>electrical signals (acquired in<br>orthogonal axes via VCG) and<br>hemodynamic signals (acquired<br>via photoplethysmography<br>(PPG)) | HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate Claris™ System v1.2<br>(K210392)<br><br>K210392:<br>Oximetry, heart rate, and<br>additional cardiovascular<br>parameters (e.g., blood pressure,<br>oxygen delivery, etc.)<br><br>K201446:<br>Electrocardiograph and<br>intracardiac electrical signals | Same – The measured<br>physiological parameters of the<br>CorVista System are a subset of<br>those measured by the secondary<br>predicate devices. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Data Displayed | Likelihood of significant<br>Coronary Artery Disease<br>(CAD) | Viz HCM (DEN230003)<br><br>Notification Flag for patients who<br>require further HCM follow-up | Different - Display of the<br>likelihood of disease is of superior<br>diagnostic value compared to a<br>notification flag used in the<br>predicate device, therefore the<br>safety and effectiveness is non-<br>inferior compared to the predicate.<br>The clinical performance of the<br>CorVista System for the intended<br>disease and output has been<br>confirmed through testing. |
| Application Site | Trunk & Digits | HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate Claris™ System v1.2<br>(K210392)<br><br>The secondary predicates have<br>application sites including the<br>Trunk (K210392) and Digits<br>(K201446). | Same – The CorVista System<br>utilizes a subset of the application<br>sites utilized by the secondary<br>predicate devices. |
| Data Output | Tablet easy-to-read display<br>(LCD), Mobile App, and Web<br>App | Viz HCM (DEN230003)<br><br>Mobile app | Different - This difference does<br>not change the intended use of the<br>device. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Hardware | Seven-Channel Lead Set,<br>PPG Sensor,<br>Capture Device (Tablet) | HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate ClarisTM System v1.2<br>(K210392)<br>The secondary predicates utilize<br>lead sets, oximeter cables,<br>computer systems, etc. | Different - This difference does<br>not change the intended use of the<br>device. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Software | CorVista Health Proprietary<br>Algorithm,<br>CorVista Health Proprietary<br>Application | Viz HCM (DEN230003)<br>Viz.ai Proprietary Algorithm,<br>Viz.ai Proprietary Application | Different - This difference does<br>not change the intended use of the<br>device. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Physical<br>Degree of Protection<br>Against Electric Shock | Type CF – Applied Part | HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate ClarisTM System v1.2<br>(K210392)<br>Type BF and CF Applied Parts<br>(K201446)<br>Type CF - Applied Part<br>(K210392) | Same - The degree of protection<br>against electrical shock is the same<br>as the secondary predicate devices<br>and is appropriate for the intended<br>use environment. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| Characteristic | Subject Device | Chosen Predicate Device with<br>Justification | Comparison |
| Functional and Safety<br>Testing | IEC 60601-1 | HemoSphere Advanced<br>Monitoring Platform, HemoSphere<br>ClearSight Module (K201446) and<br>Workmate Claris™ System v1.2<br>(K210392) | Different - This difference does<br>not change the intended use of the<br>device. All devices completed<br>Functional and Safety testing<br>pursuant to their design and<br>intended use. The safety and<br>effectiveness of the CorVista<br>System has been confirmed<br>through testing. |
| | IEC 60601-1-2 | | |
| | IEC 60601-2-25 | | |
| | IEC 80601-2-61 | | |
| | IEC 60259 | | |
| | IEC 62133 | K201446:<br>IEC 60601-1<br>IEC 60601-1-2<br>IEC 60601-1-6<br>IEC 60601-1-8<br>IEC 60601-2-34<br>IEC 60601-2-57<br>IEC 60601-2-49<br>IEC 80601-2-49<br>Wireless Co-existence<br><br>K210392:<br>IEC 60601-1<br>IEC 60601-1-2 | |
| | AIM 7351731 | | |
| | ANSI IEEE C63.27 | |…
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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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Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
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Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
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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.
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Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
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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.
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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.