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ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography

Hooman Vaseli, Ang Nan Gu, Naser Ahmadi, Michael Tsang, Andrea Fung, Nima Kondori, Armin Saadat, Purang Abolmaesumi, Teresa S.M. Tsang

2023Lecture notes in computer science16 citationsDOI

Topics & Concepts

InterpretabilityComputer scienceAmbiguityArtificial intelligenceData miningStenosisSet (abstract data type)Machine learningRadiologyMedicineProgramming languageCardiac Valve Diseases and TreatmentsInfective Endocarditis Diagnosis and ManagementPhonocardiography and Auscultation Techniques
ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography | Litcius