Cardio-TriTest vs Lung AI

Similar category, different focus. These tools serve overlapping but distinct needs. Comparability 65/100 Comparability is an AI-graded 0–100 score of how directly these two tools compete — higher means a more apples-to-apples comparison.
by Cardio-Phoenix Inc.
VS
by Multiple (e.g., RevealDx, Optellum, LungLife AI, Qure.ai, Arterys, DeepHealth, HeartLung.AI)

AI Verdict

Cardio-TriTest is a specialized 3-in-1 diagnostic device focusing on comprehensive cardiovascular disease detection through ECG, PCG, and MCG bio-signal analysis. In contrast, Lung AI by Exo is a handheld AI-powered ultrasound platform designed for real-time imaging and detection across both cardiac and pulmonary conditions. While both leverage AI for cardiac insights, Cardio-TriTest offers a multi-modal bio-signal approach for heart-specific diagnostics, whereas Lung AI provides a versatile imaging solution with broader applications including lung pathology.

Choose Cardio-TriTest if…

Choose Cardio-TriTest if your primary care clinic requires a comprehensive, multi-modal diagnostic tool for earlier and more thorough cardiovascular disease detection. This device is ideal for synchronizing and visually correlating ECG, PCG, and MCG bio-signals to provide a deeper understanding of heart health in a non-invasive manner, facilitating proactive patient management.

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Choose Lung AI if…

Choose Lung AI (integrated with the Exo Iris handheld ultrasound) if your clinical setting demands immediate, point-of-care imaging and AI-assisted diagnostics for critical real-time decisions, particularly in emergency medicine or pulmonology. This handheld solution excels at rapidly detecting conditions like pleural effusion or consolidation/atelectasis and offers automated cardiac indicators directly at the patient's bedside, even without internet connectivity.

View Lung AI →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature Cardio-TriTest Lung AI
Pricing Contact for pricing Unknown
Deployment Clinical setting (device-based) Cloud-based, integrated with existing platforms (e.g., RapidAI), and potentially on-premise.
FDA Status Cleared AI-estimated Cleared AI-estimated
HIPAA Yes AI-estimated Yes AI-estimated

Head-to-Head

AI-generated assessment across six dimensions based on each tool's documented features and compliance posture. Grounded in public data — not a substitute for hands-on evaluation.

Usability

Lung AI

Tool B emphasizes 'easy-to-use,' 'handheld,' 'intuitive workflow,' 'guided image capture,' and 'AI-powered POCUS education and training,' directly addressing user experience and ease of adoption for a broader range of users, including novices. While Tool A aims to simplify multi-modal cardiac diagnostics for general practitioners, Tool B's focus on real-time feedback and automated image acquisition significantly enhances usability, especially for point-of-care ultrasound.

Clinical Value

Lung AI

Tool B has strong, specific clinical validation data from multi-reader, multi-case studies showing improved diagnostic accuracy for lung conditions and high reliability for cardiac indicators, even for novice users. While Tool A is FDA cleared and offers a comprehensive multi-modal approach, the available information for Tool B provides more detailed and recent evidence of its direct impact on diagnostic performance and patient outcomes in specific clinical scenarios.

Pricing & Value

Tie

Both tools explicitly state 'contact for pricing,' making a direct comparison of their cost-effectiveness impossible. While Tool B's marketing materials and some user discussions suggest it aims to be affordable and cost-effective compared to traditional systems, this remains unsubstantiated by official pricing details for a definitive verdict.

Enterprise Readiness

Lung AI

Tool B demonstrates superior enterprise readiness by explicitly stating HIPAA compliance, having a Business Associate Agreement (BAA), and featuring on-device AI processing that operates without internet, ensuring robust performance in various clinical environments. Furthermore, its integration with 'Exo Works Workflow Software' for seamless documentation and review, along with meeting HITRUST and SOC2 standards, highlights a comprehensive approach to enterprise deployment and data security.

Innovation

Lung AI

While Tool A's 3-in-1 synchronized bio-signal acquisition is innovative for comprehensive cardiac assessment, Tool B's integration of real-time, on-device AI into a handheld ultrasound platform for guided image capture, quality monitoring (SweepAI), and immediate diagnostics across multiple specialties (cardiac and lung) represents a broader and more impactful innovation in point-of-care imaging. This approach significantly enhances accessibility and ease of use for advanced diagnostic capabilities.

Support & Docs

Lung AI

Tool B clearly outlines its commitment to user support and education through 'Exo U (AI-powered POCUS education and training)' and a dedicated 'Exo Support Center' offering various contact methods and documentation. Tool A provides no information regarding its support or documentation, making Tool B the clear winner in this dimension.

Feature-by-Feature

Detail beyond the Quick Comparison summary. For pricing, deployment, BAA, FDA, and HIPAA see the Overview tab.

Feature Cardio-TriTest Lung AI
Name Cardio-TriTest Lung AI
Company Cardio-Phoenix Inc. Exo
Description (Core Function) AI-powered 3-in-1 diagnostic device combining ECG, PCG, and MCG to synchronize and visually correlate heart bio-signals for earlier and more comprehensive cardiovascular disease detection in primary care. High-performance, handheld ultrasound platform that uses artificial intelligence for imaging and therapeutic applications, empowering healthcare professionals to make critical, real-time decisions.
Primary Diagnostic Modalities 3-in-1 diagnostic device (ECG, PCG, MCG) Handheld ultrasound with AI
Key AI-powered Detections/Capabilities AI-powered analysis for heart disease detection; Synchronized bio-signal acquisition; Visual correlation of heart bio-signals. AI-powered detection of pleural effusion; AI-powered detection of consolidation/atelectasis; Automated AI-based indicators for cardiac conditions (e.g., heart failure, hypertrophy); Real-time feedback and image quality monitoring (SweepAI); Guided image capture for optimal scans; On-device AI processing (operates without internet).
Specialties Cardiology, Family Medicine, Internal Medicine Cardiology, Emergency Medicine, Pulmonology

Videos

Demos, reviews, and walkthroughs featuring Cardio-TriTest and Lung AI.

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Frequently Asked Questions

Cardio-TriTest is a device-based diagnostic tool designed to provide three different types of non-invasive heart bio-signals (ECG, PCG, MCG) which are synchronized and visually correlated to aid physicians in making a broader diagnosis of cardiovascular health in a clinical setting. Lung AI, integrated with the Exo Iris handheld ultrasound, offers real-time AI-powered detection of pleural effusion, consolidation/atelectasis, and automated indicators for cardiac conditions, enabling immediate bedside insights for conditions like pneumonia, tuberculosis, and heart failure. While Cardio-TriTest focuses on comprehensive cardiovascular diagnostics through bio-signal analysis, Lung AI provides immediate, image-based diagnostic support for both cardiac and pulmonary conditions at the point of care.
While the provided information for Cardio-TriTest does not explicitly detail EHR integration, it is intended to aid physician diagnostic interpretation in a clinical setting, implying data output for clinical records. For Lung AI, the system is designed to simplify workflow by helping trained healthcare providers evaluate, quantify, and generate reports for ultrasound images, and its AI modules can be integrated as a software component into legally marketed ultrasound imaging devices, with data management considerations including data sources, collection, storage, and sequestration. Effective EHR integration and data archiving are crucial for both tools to ensure comprehensive patient records and streamline clinical operations.
Cardio-TriTest's diagnostic interpretations are significant when used in conjunction with physician over-read and other relevant patient data, and its safety and performance have been subject to extensive testing and software validation. For Lung AI, clinical studies have shown that AI assistance significantly improves diagnostic accuracy for lung ultrasound interpretation, with sensitivity gains of over 11.8% for pleural effusion and 18.4% for consolidation/atelectasis, and overall sensitivity and specificity reaching approximately 90% with AI. Exo's Cardiac and Lung AI has been developed and tested using over 100,000 scans from diverse patient populations and diagnostic types, and its lung AI reliably identifies B-lines for pulmonary edema, while cardiac AI measures left ventricular ejection fraction and stroke volume.
Cardio-TriTest is designed to synchronize and visually correlate bio-signals to make it easier for general practitioners to determine heart health, and its use is on a prescription basis by a Certified Medical Practitioner. Lung AI, integrated with Exo Iris, aims to simplify the process of obtaining and interpreting images, with features like guided image capture for optimal scans and real-time feedback (SweepAI) to monitor image quality and indicate when enough diagnostic information has been captured. Exo also offers Exo U, an AI-powered POCUS education and training platform with short videos to demonstrate correct image acquisition, suggesting a structured approach to reduce the learning curve for point-of-care ultrasound.
The provided information does not explicitly detail audit trail functionalities for Cardio-TriTest. For Lung AI, as part of a system that processes protected health information, it would typically include audit controls to track user actions, data access, and modifications for traceability and compliance. Audit trails are crucial in clinical research and healthcare for ensuring accountability, transparency, and data integrity by recording who accessed or modified data, when it happened, and what changes were made.
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