Lung AI
Overview
Lung AI by Exo is an artificial intelligence application designed to assist healthcare providers in interpreting point-of-care ultrasound (POCUS) lung scans. Running directly on the handheld Exo Iris device, the software operates on-device and real-time without requiring an active internet connection.
The tool is built for clinicians across multiple specialties—including emergency medicine, critical care, internal medicine, and pulmonology—operating in hospitals, clinics, and remote or under-resourced care settings. It integrates into the clinical workflow at the patient’s bedside, allowing providers to perform rapid diagnostic assessments of acute pulmonary symptoms such as dyspnea.
Notable Capabilities:
- Automatically detects and localizes key pulmonary features, including the presence or absence of A-lines and B-lines.
- Identifies pleural effusion and consolidation or atelectasis directly on-screen.
- Recognizes anatomical landmarks, including rib shadows and the pleural line, to guide proper probe placement.
- Provides real-time quality feedback by generating per-frame and per-clip quality scores for each lung scan to ensure reliable imaging.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered detection of pleural effusion
- AI-powered detection of consolidation/atelectasis
- Real-time feedback and image quality monitoring (SweepAI)
- Automated AI-based indicators for cardiac conditions (e.g., heart failure, hypertrophy)
- Guided image capture for optimal scans
- On-device AI processing (operates without internet)
- Pulsed-wave Doppler capabilities (on Exo Iris)
- Exo U (AI-powered POCUS education and training)
- High accuracy and validated performance across diverse patient populations
- Detection of A-lines and B-lines for pulmonary edema assessment
Use Cases
- Diagnosing lung diseases like pneumonia and tuberculosis at the bedside
- Assessing fluid status, including pulmonary edema and IVC collapsibility
- Detecting cardiac conditions such as heart failure and cardiac toxicity
- Enhancing diagnostic capabilities in emergency and critical care settings
- Supporting point-of-care ultrasound (POCUS) education and training
- Accelerating patient care pathways to treatment or discharge
What Physicians Need to Know
Leverage AI-CVD to transform routine chest and abdominal CT scans into a powerful, scalable platform for opportunistic cardiovascular and multi-system risk assessment. Pay close attention to the quantitative measurements for CAC, cardiac chamber volumes, and valve calcifications, as these can reveal silent disease and inform early intervention strategies for conditions like heart failure, atrial fibrillation, and coronary artery disease. Remember that AI-CVD provides quantitative imaging insights and does not replace diagnostic interpretation or direct clinical judgment.
AI-CVD is designed to operate as an opportunistic add-on to CT scans already being performed for other clinical indications, such as lung cancer screening CT, diagnostic chest CT, and coronary CT angiography. It aims to integrate seamlessly into existing workflows without requiring additional imaging, radiation, contrast, or workflow disruption.
Details
| Category | Cardiology AI, Radiology & Imaging AI |
| Pricing | Contact for pricing — Not available |
| Deployment | On-device (integrated with Exo Iris handheld ultrasound device) |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status |
1 AI-estimated Exo has multiple FDA 510(k) clearances for its AI applications, including cardiac, lung, bladder, hip, and thyroid. Specifically, the Lung AI (K243239) is an FDA 510(k) cleared Computer-Aided Detection (CADe) tool designed to assist in the detection of consolidation/atelectasis and pleural effusion during lung ultrasound scans. The clearance for Lung AI was granted on April 24, 2025. |
| Integrations | |
| EHR | Not specified |
| Specialties | Cardiology, Emergency Medicine, Pulmonology |
What the Web Says
AI in lung health is rapidly advancing, showing significant promise in improving the diagnosis, treatment, and management of various lung conditions like cancer, asthma, COPD, and interstitial lung diseases. It assists physicians by analyzing complex patient data, interpreting imaging, and identifying subtle patterns that might be missed by the human eye, leading to earlier and more accurate diagnoses. While AI tools are not yet meant to replace human expertise, they are proving to be valuable adjuncts in clinical practice, enhancing efficiency and potentially improving patient outcomes.
Overall: PositiveStrengths
- Improved accuracy in detecting lung nodules and other abnormalities on imaging (X-rays, CT scans, ultrasound).
- Earlier detection of lung cancer, potentially leading to better patient outcomes and increased survival rates.
- Assists physicians in making better diagnostic and treatment decisions by analyzing complex patient information.
- Reduces physician workload and fatigue-related errors, allowing more time for patient care.
- Enhances diagnostic accuracy for various lung diseases, particularly benefiting less experienced clinicians.
- Potential for personalized treatment plans based on genomic and molecular data analysis.
Limitations
- Potential for bias if AI is trained on incomplete or unrepresentative data, leading to unsuitable recommendations for certain patient groups.
- Ethical considerations, regulatory hurdles, and the need for ongoing research and validation in real-world clinical settings.
- AI tools may have lower specificity compared to radiologists in some cases, leading to false positives.
- Integration into existing clinical workflows can be challenging, and AI prioritization alone may not always speed up the entire diagnostic pathway.
- Lack of empathy and understanding of emotional/psychological aspects of patient experience.
- Accessibility issues for patients without internet, smartphones, or digital skills.
Based on reviews from: Breathe, Sathyakumar, PMC, Reddit, Health IT Answers, Viz.ai, Healthcare Today, University College London Hospitals, AuntMinnie, Today's Clinical Lab, YouTube, arXiv, G2, Capterra, Blastra
Last updated: 2026-07-19
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Press & Coverage
Videos
Product demos, reviews, and walkthroughs for Lung AI.
Lung AI FDA-Cleared
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Lung Zone Right 4 with Handheld Ultrasound Exo Irisu00ae
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Introduction to AI for Handheld Ultrasound Exo Irisu00ae
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Frequently Asked Questions
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