Lung AI vs Tempus ECG-AF

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 Exo
VS
by Tempus AI, Inc.

AI Verdict

These tools are adjacent competitors, both leveraging AI in cardiology but with distinct approaches. Tool A, Lung AI, focuses on real-time, on-device ultrasound imaging for immediate cardiac and lung diagnostics, suitable for point-of-care scenarios. In contrast, Tempus ECG-AF is a software solution that analyzes existing 12-lead ECGs to predict the risk of future atrial fibrillation in specific patient populations, integrating with established healthcare facility systems.

Choose Lung AI if…

Choose Lung AI if you require immediate, real-time diagnostic imaging at the point of care, particularly for rapid assessment of lung and cardiac conditions. Its handheld, on-device AI processing makes it ideal for emergency medicine, critical care, or remote settings where quick visual confirmation and decision-making are paramount, even without internet connectivity.

View Lung AI →

Choose Tempus ECG-AF if…

Choose Tempus ECG-AF if your objective is to proactively identify older patients at increased risk of developing new-onset atrial fibrillation within the next year, leveraging existing 12-lead ECG data. This software solution is best suited for integration into cardiology, geriatrics, or internal medicine workflows to support earlier intervention and follow-up for at-risk individuals aged 65 or older.

View Tempus ECG-AF →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature Lung AI Tempus ECG-AF
Pricing Contact for pricing Contact vendor
Deployment On-device (integrated with Exo Iris handheld ultrasound device) Software solution, integrated into healthcare facility systems with advanced cardiology algorithms.
BAA Available Yes AI-estimated Yes AI-estimated
FDA Status 1 AI-estimated Yes AI-estimated
HIPAA Yes AI-estimated Yes AI-estimated

Feature-by-Feature

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

Feature Lung AI Tempus ECG-AF
Product Name Lung AI Tempus ECG-AF
Company Exo Tempus AI, Inc.
Primary Function High-performance, handheld ultrasound platform with AI for imaging and therapeutic applications, focusing on cardiac and lung scanning. FDA-cleared AI-based algorithm that analyzes 12-lead ECG recordings to identify patients aged 65 or older at increased risk of developing atrial fibrillation/flutter (AF) within the next 12 months.
Target Patient Population/Use Case Smarter Cardiac and Lung Scanning for real-time decisions and improved patient outcomes. Patients aged 65 or older without pre-existing AF, pacemakers, ICDs, or recent cardiac surgery, to identify increased risk of developing AF within 12 months.
Core AI Capabilities AI-powered detection of pleural effusion, AI-powered detection of consolidation/atelectasis, automated AI-based indicators for cardiac conditions (e.g., heart failure, hypertrophy). AI-based algorithm for 12-lead ECG analysis, detects signs associated with new onset Atrial Fibrillation (AF) within 12 months.
Specialties Supported Cardiology, Emergency Medicine, Pulmonology Cardiology, Geriatrics, Internal Medicine

Videos

Demos, reviews, and walkthroughs featuring Lung AI and Tempus ECG-AF.

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Frequently Asked Questions

Lung AI integrates into point-of-care workflows as a handheld ultrasound platform, enabling real-time decisions for cardiac and lung scanning through AI-powered detection. Tempus ECG-AF integrates by analyzing existing 12-lead ECG recordings to identify patients at increased risk of developing AF/flutter within 12 months, supporting earlier identification and follow-up.
Lung AI is deployed on-device, integrated with the Exo Iris handheld ultrasound device, and the provided information does not detail direct EHR integration. Tempus ECG-AF is a software solution designed to be integrated into healthcare facility systems with advanced cardiology algorithms, suggesting a more direct and systematic integration for result transfer.
Lung AI provides AI-powered detection of pleural effusion and consolidation/atelectasis, along with automated AI-based indicators for cardiac conditions like heart failure and hypertrophy, for general patient use. Tempus ECG-AF identifies patients aged 65 or older without pre-existing AF, pacemakers, ICDs, or recent cardiac surgery, who are at increased risk of developing AF/flutter within the next 12 months.
Lung AI emphasizes ease of use with guided image capture and offers Exo U, an AI-powered POCUS education and training program to support clinicians. For Tempus ECG-AF, the learning curve would primarily involve understanding how to interpret its risk assessment results in conjunction with other clinical data, as it's an analytical algorithm.
Lung AI features on-device AI processing, meaning it operates without an internet connection, which inherently enhances data security by keeping sensitive patient information local during analysis. Tempus ECG-AF is a software solution integrated into healthcare facility systems, implying reliance on the facility's existing security infrastructure for data processing.
Lung AI, as a handheld device with on-device AI processing, offers flexibility for multi-site deployment, potentially simplifying network dependency considerations at each location. Tempus ECG-AF, being a software solution integrated into healthcare facility systems, would require integrating the algorithm into the IT infrastructure of each facility, likely involving coordination with local IT and cardiology departments.
Lung AI provides real-time feedback and AI processing on-device, allowing for immediate diagnostic insights and real-time decisions at the point of care, leading to rapid clinical value. Tempus ECG-AF offers value by proactively identifying patients at increased risk of developing AF/flutter within the next 12 months, supporting earlier intervention and follow-up for improved patient management.

Backers

Who funded each tool's parent company.

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