Autoplaque vs Lung AI

Similar category, different focus. These tools serve overlapping but distinct needs. Comparability 60/100 Comparability is an AI-graded 0–100 score of how directly these two tools compete — higher means a more apples-to-apples comparison.

Autoplaque

by Cedars-Sinai Medical Center: AIM

Lung AI

by Exo

AI Verdict

Autoplaque and Lung AI are adjacent competitors, both leveraging AI for medical image analysis but focusing on different anatomical areas and imaging modalities. Autoplaque specializes in quantitative analysis of coronary plaques and luminal stenoses from CT angiography images to aid in heart attack risk prediction. Lung AI, on the other hand, utilizes AI with a handheld ultrasound platform for cardiac and lung scanning, specifically for detecting conditions like pleural effusion and consolidation/atelectasis, and providing real-time feedback.

Choose Autoplaque if…

Choose Autoplaque if you need detailed, quantitative analysis of coronary plaques and luminal stenoses from CT angiography images. This workstation-based software is ideal for cardiologists and radiologists seeking to precisely characterize atherosclerotic plaque, measure vessel dimensions, and aid in heart attack risk prediction and treatment planning based on comprehensive CT data.

View Autoplaque →

Choose Lung AI if…

Choose Lung AI if you require a portable, real-time AI-powered ultrasound solution for immediate point-of-care diagnostics, particularly in emergency medicine, pulmonology, or cardiology. This on-device AI, integrated with the Exo Iris handheld ultrasound, excels at quickly detecting conditions like pleural effusion and consolidation/atelectasis, and provides automated indicators for cardiac conditions such as heart failure, even without internet access.

View Lung AI →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature	Autoplaque	Lung AI
Pricing	Not disclosed	Contact for pricing
Deployment	Workstation-based software, runs on Windows or Mac computer platforms	On-device (integrated with Exo Iris handheld ultrasound device)
BAA Available	Unknown	Yes AI-estimated
FDA Status	1 AI-estimated	1 AI-estimated
HIPAA	Unknown	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 (Lung AI) is integrated into a handheld ultrasound device and designed for user-friendliness by non-experts, operating on-device without internet. This makes it highly portable and accessible for real-time decision-making at the point of care. Tool A (Autoplaque) is workstation-based software, requiring installation on a computer, which suggests a less immediate and portable user experience.

Clinical Value

Lung AI

Tool B (Lung AI) offers real-time AI-powered detection of pleural effusion and consolidation/atelectasis, with studies showing improved diagnostic accuracy for clinicians, particularly less experienced users. Tool A (Autoplaque) provides quantitative analysis of coronary plaques and luminal stenoses from CT angiography, aiding in heart attack risk prediction, and has demonstrated excellent agreement with expert readers. However, the real-time, on-device nature of Tool B for immediate critical decisions in various settings gives it a slight edge in direct clinical impact.

Pricing & Value

Tie

Both tools lack transparent pricing information, with Tool A stating 'not disclosed' and Tool B stating 'contact for pricing.' Without specific pricing details, it is impossible to definitively compare their value propositions.

Enterprise Readiness

Lung AI

Tool B (Lung AI) is HIPAA compliant and has a Business Associate Agreement (BAA), indicating a clear readiness for enterprise deployment with appropriate data security and privacy measures. Tool A (Autoplaque) does not specify HIPAA compliance or BAA availability, which could be a barrier for enterprise adoption in healthcare settings.

Innovation

Lung AI

Tool B (Lung AI) demonstrates higher innovation by integrating AI directly into a high-performance, handheld ultrasound platform for real-time, on-device processing, enabling immediate critical decisions at the point of care. Tool A (Autoplaque) is a workstation-based software, which, while advanced in its analytical capabilities, represents a more traditional deployment model for AI in medical imaging.

Support & Docs

Tie

Neither tool provides specific details regarding their support services or documentation in the provided information. Therefore, it is not possible to determine a 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	Autoplaque	Lung AI
Tool Name	Autoplaque	Lung AI
Company	Cedars-Sinai Medical Center: AIM	Exo
Description	AI-powered software for quantitative analysis of coronary plaques and luminal stenoses from CT angiography images, aiding in heart attack risk prediction and treatment guidance.	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.
Key Features	AI-powered quantitative analysis of atherosclerotic plaque; Detection and characterization of coronary artery plaque; Measurement of luminal stenoses; Analysis of coronary anatomy and pathology from CT Angiographic images; Workstation-based post-processing application; Automated vessel, plaque, and lumen segmentation (reviewable and editable by clinician); Review of heart and coronary vessels in Multiplanar Reformatting (MPR), curved MPR, and straightened MPR views; Measurement of vessel diameter and area.	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).
Specialties	Cardiology, Radiology	Cardiology, Emergency Medicine, Pulmonology

Videos

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

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Frequently Asked Questions

How do Autoplaque and Lung AI integrate into existing clinical workflows and EHR systems?

Autoplaque is a workstation-based post-processing application designed to integrate into routine CCTA workflows, functioning as a second reader and clinical decision support tool. It aims to reduce interobserver variability and interpretative error by providing automated and objective results. Lung AI, integrated with the Exo Iris handheld ultrasound device, processes AI on-device, meaning it operates without an internet connection. While the description doesn't explicitly detail EHR integration for Lung AI, AI-powered solutions in lung health often leverage natural language processing (NLP) to evaluate EHR data for patient identification and management.

What are the reported accuracy and sensitivity metrics for Autoplaque and Lung AI?

Autoplaque provides quantitative analysis of coronary plaques and luminal stenoses, with its latest version offering fully automated case preparation and end-to-end quantification of plaque burden and stenosis grading. While specific accuracy and sensitivity figures for Autoplaque are not provided in the given information, deep learning-based plaque volume measurements have shown independent prognostic value for future cardiac events. For Lung AI, studies indicate high accuracy for detecting pleural effusion and consolidation/atelectasis, with sensitivities of 0.967 and 0.968 respectively, and specificities of 0.912 and 0.945. AI-assisted lung nodule detection in general has shown increased sensitivity compared to radiologists, though sometimes with lower specificity.

Which medical specialties are these tools best suited for, and what specific clinical problems do they address?

Autoplaque is primarily suited for Cardiology and Radiology, focusing on the quantitative analysis of coronary plaques and luminal stenoses from CT angiography images to aid in heart attack risk prediction and treatment guidance. Lung AI is designed for Cardiology, Emergency Medicine, and Pulmonology, offering AI-powered detection of pleural effusion and consolidation/atelectasis, real-time feedback for image quality, and automated indicators for cardiac conditions. It aims to make medical imaging more accessible and support real-time critical decisions.

What is the typical learning curve for physicians adopting Autoplaque or Lung AI?

Autoplaque is described as a semi-automated, on-site, supervised-learning system that requires user interaction, with editing tools available for automated segmentations. This suggests some initial training and interaction are needed, though the fully automated case preparation in its latest version aims to streamline the process. Lung AI, with its guided image capture for optimal scans and on-device AI processing, is designed to be easy-to-use. Studies have shown that AI assistance can enable novice users of lung ultrasound to acquire diagnostic-quality images, suggesting a reduced learning curve for image acquisition and interpretation.

What kind of customer support and training can physicians expect for these tools?

The provided information does not explicitly detail the customer support or training programs for either Autoplaque or Lung AI. However, for Autoplaque, it is stated that users should be appropriately trained in the software's functions, capabilities, and limitations. For Lung AI, the 'Exo U (AI-powered POCUS education and training)' feature suggests that comprehensive education and training are part of their offering, which would likely include support.

Are there features for audit trails or tracking AI-assisted decisions within these tools?

The provided descriptions do not explicitly mention audit-trail features for either Autoplaque or Lung AI. However, in general, AI tools in healthcare are increasingly being integrated with features that support clinical decision-making and workflow, and robust systems often include mechanisms for tracking and auditing. For example, some AI systems for lung nodule detection provide structured reporting with pre-populated Lung-RADS templates, which can contribute to a traceable workflow.

What are the considerations for rolling out Autoplaque or Lung AI across multiple clinical sites?

Autoplaque is a workstation-based software, running on Windows or Mac platforms, which implies that multi-site rollout would involve individual workstation installations and potentially network considerations for data transfer if not processed locally. Lung AI, being integrated with a handheld ultrasound device and featuring on-device AI processing, offers a more portable and potentially decentralized deployment model. This on-device processing means it operates without an internet connection, which could simplify deployment in various settings, including those with limited connectivity. Successful multi-site AI deployments often involve a multifaceted approach, including centralized navigation and innovative technologies to support system-wide implementation.