EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography
Echocardiography is the most widely used non-invasive cardiac imaging modality, providing essential information for cardiovascular diagnosis. Interpreting an echocardiogram requires synthesizing complementary evidence across multiple heart views to identify abnormalities and produce structured clinical reports. While recent efforts focus on improving classification performance, most models lack explicit diagnostic reasoning and spatially grounded anatomical evidence, limiting clinician trust. We present EchoSonar-R, a multi-view reasoning-enabled vision-language model that jointly performs mul
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- LinkedLinked via unknownUsing AI to help physicians diagnose rare genetic diseases affecting children →
- PossiblePossibly related (embedding) · 46%DIAGNijmegen/rse-grand-challenge →
- PossiblePossibly related (embedding) · 45%Co-pilot, Not Autopilot: A Practical Method for Using Large Language Models in Interventional Cardiology - EMJ →
- FuzzySimilar title/name (fuzzy) · 59%rasbt/reasoning-from-scratch →
“Fuzzy title match (0.73): “EchoSonar-R: A Multi-View Reasoning-Enabled Model for Diseas” ≈ “rasbt/reasoning-from-scratch””
- PossiblePossibly related (embedding) · 55%Artificial Intelligence Across the Echocardiographic Workflow: A Narrative Review for Clinicians - Cureus →
