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Deep learning in primary care health records to predict incident heart failure from temporal and contextual representation of antecedent risk factors

9 May 2026 (08:00 - 12:45)
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Congress Presentation Part of: Digital detection and diagnostic pathways in heart failure Electronic Health Records & Hospital Information Systems Delegates Premium Access Heart Failure 2026 Heart Failure Association (HFA)

About the speaker

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Miss Sashi Kiran Mahapatra

University of Leeds, Leeds (United Kingdom of Great Britain & Northern Ireland)

6 More presentations in this session

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Relevance and feasibility of artificial intelligence-assisted echocardiography for left ventricular ejection fraction assessment in geriatric patients
Mr A. Hacil (Paris, FR)
Abstract
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Can decentralized community rapid cardiac ultrasound triage reduce carbon footprint? Environmental insights from the Heart2Miss study
Doctor J. Chunggat (Kuching, MY)
Abstract
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THINK-HF: development, feasibility, and usability study of an intelligent electronic health record integrated tool for early heart failure diagnosis in primary care
Mrs K. Barber (Leicester, GB)
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Addressing barriers to digital health technology adoption for cardiovascular disease prevention: preliminary findings from the ACHIEVE-Digital global qualitative survey
Miss J. Leroux (Montreal, CA)
Abstract
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ICD-10-based machine learning classification model of left ventricular systolic dysfunction: a population-based risk stratification evaluation in 83,357 patients with acute coronary syndrome
Miss A. Cosa (Hospitalet de Llobregat, ES)
Abstract

Access the full session

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Digital detection and diagnostic pathways in heart failure

The Event

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Heart Failure 2026

9 May - 12 May 2026
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ESC 365 is supported by

novartis Explore sponsored resources