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An explainable calibrated concept bottleneck model with evidence-constrained large language model reporting for multi-label valvular heart disease screening from 12-lead ECGs

31 August 2026 (10:15 - 11:00)
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Congress Presentation Part of: Artificial intelligence-powered assessment of cardiac function Large Language Model ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Mr Zafar Ahmad

National University of Sciences and Technology (NUST), Islamabad (Pakistan)

5 More presentations in this session

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Development and external validation of an AI- model to triage echocardiograms
Associate Professor J. Strom (Boston, US)
Abstract
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Effect of mHealth on the prognosis of patients with heart failure according to left ventricular ejection fraction: subanalysis of the HERMeS Trial
Doctor A. Pons Riverola (Barcelona, ES)
Abstract
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ncLVMass-Net: dedicated AI for left ventricular myocardium segmentation and hypertrophy detection from non-contrast cardiac CT
Professor T. Wang (Taipei, TW)
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ECG-based transformer model predicts future left ventricular ejection fraction deterioration: from cross-sectional screening to longitudinal risk stratification
Doctor S. Lee (Seoul, KR)
Abstract
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Plasma proteomics integration reveals foxO and relaxin signaling as primary drivers of myocardial radiomic heterogeneity in end-stage HFrEF
Mr P. Laba (PL)
Abstract

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Artificial intelligence-powered assessment of cardiac function

The Event

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ESC Congress 2026

31 August 2026 10:15 CET
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