eMurmur ID vs EchoNext

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 CSD Labs GmbH
VS
by Pathway Labs

AI Verdict

eMurmur ID and EchoNext are adjacent tools in cardiology AI, both offering clinical decision support. eMurmur ID focuses on real-time heart murmur detection and classification using electronic stethoscopes, while EchoNext analyzes standard ECGs to detect hidden structural heart disease. The choice between them depends on whether the primary need is for auscultation-based murmur analysis or ECG-based structural heart disease screening.

Choose eMurmur ID if…

Choose eMurmur ID if your primary need is AI-powered detection and classification of heart murmurs using an electronic stethoscope, particularly for real-time decision support during auscultation or for remote consultations. It's ideal for healthcare providers who want to enhance their cardiac auscultation skills, reduce inappropriate referrals for echocardiograms, and manage patient heart sound data through a mobile app and web portal.

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Choose EchoNext if…

Choose EchoNext if you need an FDA-cleared AI tool to analyze standard ECGs for the detection of hidden structural heart disease, including heart failure, valve disease, and pulmonary hypertension. This tool is best suited for broad-access screening in various clinical settings, from major hospitals to community practices, to identify high-risk patients who may require further diagnostic imaging like echocardiograms.

View EchoNext →

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Quick Comparison

Feature eMurmur ID EchoNext
Pricing Contact vendor Starts at $600/month
Deployment Mobile and cloud (SaaS), with options for on-premise and hybrid deployments. Available through the OpenEvidence clinical decision support platform.
BAA Available Unknown Yes AI-estimated
FDA Status 1 AI-estimated Yes 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

eMurmur ID

eMurmur ID offers a mobile app and web portal for recording, displaying, and managing heart sounds, and is compatible with various third-party electronic stethoscopes, providing flexibility for users. EchoNext is deployed through the OpenEvidence platform, which is a clinical decision support platform used by many physicians, suggesting a potentially integrated but less direct user experience.

Clinical Value

EchoNext

EchoNext has demonstrated superior accuracy in detecting structural heart disease from ECGs compared to cardiologists, even when cardiologists were assisted by AI. It was trained on a massive dataset of over 1.2 million ECG-echocardiogram pairs and has shown high accuracy in identifying a range of structural heart problems. eMurmur ID also shows high sensitivity and specificity in detecting heart murmurs, but EchoNext's ability to detect a broader range of 'hidden' structural heart diseases from a standard ECG, a widely available and inexpensive test, suggests a potentially greater clinical impact.

Pricing & Value

EchoNext

EchoNext provides transparent tiered pricing starting at $600/month, with discounts for annual plans and clear details on implementation fees and add-ons. eMurmur ID's pricing is 'contact vendor,' which offers less transparency upfront.

Enterprise Readiness

EchoNext

EchoNext is designed for broad access, from major hospitals to community practices, and is deployed through the OpenEvidence clinical decision support platform, which is used by 650,000 U.S. physicians, indicating strong enterprise integration and scalability. eMurmur ID offers mobile and cloud deployment with options for on-premise and hybrid, and is HIPAA compliant with BAA, but its enterprise reach isn't as explicitly detailed.

Innovation

EchoNext

EchoNext is highlighted as the world's first FDA-approved AI detection tool that analyzes standard ECGs to detect hidden structural heart disease, a capability previously not possible with ECGs alone. This represents a significant advancement in leveraging a common, inexpensive test for early detection of complex cardiac conditions. eMurmur ID is innovative in its AI-powered heart murmur detection using electronic stethoscopes, but EchoNext's ability to extract such detailed structural information from ECGs is a newer and more disruptive application of AI in cardiology.

Support & Docs

Tie

Neither the provided structured facts nor the web search results offer specific details about the ongoing customer support, training programs, or comprehensive documentation for either eMurmur ID or EchoNext. While eMurmur mentions 'eMurmur University' and 'eMurmur Primer' for educational purposes, these are distinct from direct product support. Therefore, it is difficult to definitively pick 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 eMurmur ID EchoNext
Tool Name eMurmur ID EchoNext
Company CSD Labs GmbH Pathway Labs
Description AI-powered mobile and cloud solution for detecting and classifying heart murmurs using a third-party electronic stethoscope, providing decision support for healthcare providers. EchoNext is an FDA-cleared AI tool from Pathway Labs that analyzes standard ECGs to detect hidden structural heart disease, including heart failure, valve disease, and pulmonary hypertension.
Key Features AI-based analytics for heart murmur detection and classification, mobile app for recording and displaying heart sounds, web portal for data management and review, operates with 3rd party electronic stethoscopes, identifies pathologic and innocent heart murmurs, absence of murmur, S1, S2 heart sounds, real-time feedback/analysis results within seconds, patient data management, clinical decision support. AI-powered ECG analysis, detection of hidden structural heart disease, identifies heart failure risk, screens for valve disease, detects pulmonary hypertension indicators, utilizes standard 12-lead ECGs, FDA-cleared technology, non-invasive diagnostic support.
Specialties Cardiology, Family Medicine, Pediatrics Cardiology, Family Medicine, Hospital Medicine, Internal Medicine

Videos

Demos, reviews, and walkthroughs featuring eMurmur ID and EchoNext.

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Frequently Asked Questions

eMurmur ID is designed to seamlessly integrate into a healthcare practitioner's workflow for cardiac auscultation, providing real-time feedback within seconds. It operates with third-party electronic stethoscopes and offers a mobile app and web portal for flexibility. EchoNext analyzes standard 12-lead ECGs and is available through the OpenEvidence clinical decision support platform, which is used by many physicians, suggesting it can be incorporated into existing digital workflows.
eMurmur ID allows for EHR integration by providing a unique permalink for each recording that can be copied directly into a patient's EHR or accessed via a summary PDF report from the web portal. EchoNext is deployed through the OpenEvidence clinical decision support platform, which aims to put its screening output in front of physicians using tools they already utilize at the point of care, implying a level of integration with existing clinical systems.
eMurmur ID has demonstrated high sensitivity and specificity for detecting pathologic heart murmurs, with studies showing 93% sensitivity and 81% specificity, and an overall accuracy of 88% in one comprehensive evaluation. In a pilot study with children, it achieved 87% sensitivity and 100% specificity for differentiating pathologic from innocent murmurs. EchoNext, in a retrospective analysis, detected structural heart disease with an AUROC of 85.2% and an AUPRC of 78.5%. In a comparison with cardiologists, EchoNext alone achieved 77% accuracy, while cardiologists achieved 64% accuracy.
eMurmur ID is suitable for Cardiology, Family Medicine, and Pediatrics, serving as a decision support tool for detecting and classifying heart murmurs. It can help reduce inappropriate referrals for echocardiograms by distinguishing innocent from pathological murmurs. EchoNext is designed for Cardiology, Family Medicine, Hospital Medicine, and Internal Medicine, focusing on detecting hidden structural heart disease, including heart failure, valve disease, and pulmonary hypertension, from standard ECGs. It aims to identify high-risk patients who would benefit from follow-up imaging, potentially before symptoms present.
eMurmur offers educational solutions like eMurmur University and eMurmur Primer to help teach and refresh heart sound recognition skills. The company emphasizes evidence-based solutions and team collaboration. While specific details on EchoNext's direct support are not provided, its deployment through the OpenEvidence platform suggests that support may be integrated within that ecosystem, which aims to facilitate the use of AI in clinical practice.
eMurmur ID provides standardized documentation of auscultation findings and offers a web portal for data management and review. Each recording has a unique permalink that can be used for documentation and access. The platform also supports asynchronous specialist review through an eConsult workflow, where recordings can be captured and later reviewed. Information regarding specific audit-trail features for EchoNext is not detailed in the provided information.
eMurmur has been validated through several clinical studies and pilot programs, including at Johns Hopkins University and Children's Hospital of Eastern Ontario. They have also been involved in projects like the UK Independent Community Pharmacy Awards for early detection of valve disease. EchoNext has been evaluated in retrospective analyses across eight hospitals and in a 100-patient pilot study, with findings published in Nature. Pathway Labs is also initiating CACTUS, a large cardiovascular AI randomized controlled trial across eight emergency departments.
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