ESC 365 - Deep learning in electronic health records to predict incident heart failure by modelling temporal dependencies of antecedent risk factors

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Deep learning in electronic health records to predict incident heart failure by modelling temporal dependencies of antecedent risk factors

Session: Artificial intelligence and diagnostic tools

Topic: m-Health & Mobile Apps

Speaker: Miss S. Mahapatra (Leeds, GB)

Event: Heart Failure 2025

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About the speaker

Miss Sashi Kiran Mahapatra

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

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5 more presentations in this session

Evaluating a large language model's ability to recommend guideline-directed medical therapy for heart failure: a pilot study

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Stratification of patients with heart failure referred to cardiology at higher risk of 1-year heart failure admission or mortality by a machine learning algorithm

Speaker: Professor J. Gonzalez Juanatey (Santiago de Compostela, ES)

Using AI to identify left ventricular ejection fraction from the ECG

Speaker: Associate Professor M. Ciccarelli (Salerno, IT)

Pro-BNP variation as a risk marker of ventricular arrythmias in CRT patients

Speaker: Doctor L. Sousa Azevedo (Vila Real, PT)

Improvement of biomarkers is associated with improved patient quality-of-life measures after heart failure hospitalisation: a sub-study of the Medly-AID randomised controlled trial

Speaker: Doctor D. Brahmbhatt (Toronto, CA)

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Artificial intelligence and diagnostic tools

Speakers: Miss S. Mahapatra, Mr J. Valk, Professor J. Gonzalez Juanatey, Associate Professor M. Ciccarelli, Doctor L. Sousa Azevedo...

About the event

Heart Failure 2025

17 May - 20 May 2025

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