Strain AI vs Lung AI

Similar category, different focus. These tools serve overlapping but distinct needs. Comparability 70/100 Comparability is an AI-graded 0–100 score of how directly these two tools compete — higher means a more apples-to-apples comparison.

Strain AI

by Exo

Lung AI

by Multiple (e.g., RevealDx, Optellum, LungLife AI, Qure.ai, Arterys, DeepHealth, HeartLung.AI)

AI Verdict

Tool A (Strain AI) is specifically designed for detailed cardiac function assessment through Global Longitudinal Strain (GLS) analysis, aiding in the detection of conditions like heart failure and cardiotoxicity. Tool B (Lung AI), while also offering automated AI-based indicators for cardiac conditions, primarily focuses on AI-powered detection of lung conditions such as pleural effusion and consolidation/atelectasis. Therefore, Strain AI is suited for specialized cardiac strain analysis, while Lung AI is geared towards broader lung and general cardiac screening and imaging support.

Choose Strain AI if…

Choose Strain AI if your primary need is a precise, quantitative assessment of adult cardiac function, specifically Global Longitudinal Strain (GLS), to aid in the early detection and management of conditions like heart failure and cardiotoxicity. This tool is ideal for cardiologists and oncologists requiring detailed, AI-powered analysis of cardiac ultrasound images without manual interpretation.

View Strain AI →

Choose Lung AI if…

Choose Lung AI if you require a versatile, handheld AI ultrasound solution for rapid, real-time diagnostic decisions at the point of care, particularly in emergency medicine or pulmonology settings. This tool excels in quickly identifying lung pathologies such as pleural effusion and consolidation, while also offering AI-based indicators for cardiac conditions and guided image capture for optimal scans.

View Lung AI →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature	Strain AI	Lung AI
Pricing	Contact for pricing	Unknown
Deployment	On-device AI, operates without internet connection.	Cloud-based, integrated with existing platforms (e.g., RapidAI), and potentially on-premise.
BAA Available	Yes AI-estimated	Unknown
FDA Status	Yes 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 explicitly highlights features like 'easy-to-use medical imaging,' 'real-time feedback and image quality monitoring (SweepAI),' and 'guided image capture for optimal scans.' These directly enhance the user experience and simplify the entire point-of-care ultrasound workflow, making it more accessible for various healthcare professionals.

Clinical Value

Lung AI

While Tool A offers a valuable, specific quantitative measure (GLS) for cardiac assessment, Tool B provides a broader range of FDA-cleared AI-powered detections for multiple critical lung conditions (pleural effusion, consolidation/atelectasis) and cardiac conditions (heart failure, hypertrophy). This wider diagnostic utility across diverse point-of-care scenarios gives Tool B a slight edge in overall clinical value.

Pricing & Value

Tie

Both tools have opaque pricing models, requiring direct contact for details. Without any specific pricing information or licensing structures, it is impossible to conduct a meaningful comparison of their cost-effectiveness or overall value proposition.

Enterprise Readiness

Strain AI

Both tools demonstrate strong enterprise readiness with HIPAA compliance, BAA availability, and on-device AI processing. However, Tool A's stated ability to 'integrate with existing ultrasound devices' offers greater flexibility for enterprises with diverse hardware infrastructures, potentially simplifying adoption and reducing integration costs compared to Tool B, which is integrated with the Exo Iris device.

Innovation

Lung AI

Both tools are innovative in their application of AI to handheld ultrasound. However, Tool B's comprehensive approach, which includes AI for guided image capture, real-time image quality feedback (SweepAI), and integrated AI-powered education (Exo U), represents a broader innovation in making POCUS more accessible, reliable, and user-friendly across the entire workflow.

Support & Docs

Lung AI

Tool B explicitly lists 'Exo U (AI-powered POCUS education and training)' as a key feature, directly enhancing user support and competency. While Exo as a company provides general support and documentation, Tool B's integrated educational component offers a distinct advantage in fostering user proficiency and adoption.

Feature-by-Feature

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

Feature	Strain AI	Lung AI
Primary Function	Analyzes cardiac ultrasound images to measure Global Longitudinal Strain (GLS), aiding physicians in assessing heart function and detecting conditions like heart failure and cardiotoxicity in adult patients.	High-performance, handheld ultrasound platform that uses artificial intelligence for imaging and therapeutic applications, empowering healthcare professionals to make critical, real-time decisions that improve patient outcomes.
Specific AI Measurement/Detection	Measures Global Longitudinal Strain (GLS); Aids in detecting heart failure (CHF, HFpEF, HFrEF) and hypertrophy; Assists in detecting cardiotoxicity.	AI-powered detection of pleural effusion; AI-powered detection of consolidation/atelectasis; Automated AI-based indicators for cardiac conditions (e.g., heart failure, hypertrophy).
Supported Specialties	Cardiology, Oncology, Radiology	Cardiology, Emergency Medicine, Pulmonology
Real-time Insights/Feedback	Delivers real-time, on-device AI insights.	Real-time feedback and image quality monitoring (SweepAI).
Device Integration/Specificity	Integrates with existing ultrasound devices.	Integrated with Exo Iris handheld ultrasound device.

Videos

Demos, reviews, and walkthroughs featuring Strain AI and Lung AI.

Loading videos…

Videos need JavaScript to load. Search YouTube directly →

View all on YouTube

Frequently Asked Questions

How do these tools integrate into a physician's existing workflow and with their current EHR system, considering Strain AI's compatibility with existing ultrasound devices versus Lung AI's integration with the Exo Iris handheld device?

Strain AI is designed as software to be integrated into existing, legally marketed ultrasound imaging devices, functioning as a post-processing tool for cardiac ultrasound images. Lung AI is integrated with the Exo Iris handheld ultrasound device, which can seamlessly send and store exams to Exo Works cloud, PACS, or Vendor-Neutral Archive (VNA) via DICOM or local network storage, and can expand connection to EHR for exam storage and billing with the Enterprise package of Exo Works.

What are the specific clinical accuracy and sensitivity metrics for the AI detections and measurements provided by Strain AI (GLS) versus Lung AI (pleural effusion, consolidation, cardiac indicators)?

Strain AI provides quantitative Global Longitudinal Strain (GLS) measurements to aid in assessing heart function and detecting conditions like heart failure and cardiotoxicity. Lung AI has demonstrated high accuracy in detecting pleural effusion with a sensitivity of 0.967 and specificity of 0.912, and for consolidation/atelectasis with a sensitivity of 0.968 and specificity of 0.945, based on a per-image analysis. In a multi-reader, multi-case study, AI support for pleural effusion led to an 18% improvement in sensitivity and for consolidation/atelectasis, a 16% boost in sensitivity.

Beyond the listed specialties, what specific clinical scenarios or patient populations are each tool best suited for, particularly when considering Strain AI's focus on quantitative GLS versus Lung AI's broader POCUS applications?

Strain AI is particularly vital for spotting Heart Failure with preserved Ejection Fraction (HFpEF) and for monitoring cardiotoxicity in oncology patients undergoing chemotherapy. Lung AI, with its real-time indicators for pleural effusion and consolidation/atelectasis, is well-suited for rapid bedside detection of lung diseases like pneumonia and tuberculosis, especially in emergency departments and intensive care units.

How do the features like 'guided image capture' and 'Exo U' in Lung AI compare to Strain AI's 'diagnostic evaluation without manual image interpretation' in terms of reducing the learning curve for new users and accelerating time-to-value?

Lung AI's 'guided image capture' and 'Exo U' POCUS education platform, which offers short videos on obtaining correct ultrasound images, are designed to simplify the process of acquiring and interpreting images, particularly benefiting less experienced users. Strain AI supports diagnostic evaluation without manual image interpretation by providing quantitative GLS measurements, aiming to streamline the interpretation phase for physicians.

What support and resources are available for multi-site rollouts, and can we access customer references to understand real-world implementation experiences and support quality?

Exo provides customer technical support through its Global Support Services department, which handles tickets and offers assistance for installation, usage, and problem diagnosis. While the provided information highlights Exo's support structure, details regarding specific resources for multi-site rollouts and the availability of customer references for real-world implementation experiences are not explicitly detailed for these particular AI tools.