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Machine learning-based identification of patient clusters with distinct cardiac chronotropic responses during exercise

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Ms Rose Tchala Sare

Paris (France)
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5 more presentations in this session

Leveraging structural equation modeling and machine learning on large-scale metabolomic data to uncover atrial fibrillation risks

Speaker: Mr J. Versnjak (Berlin, DE)

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Personalized prediction of aPTT responses to unfractionated heparin for ICU patients using a novel machine learning pipeline in a multi-cohort international study

Speaker: Mr M. Ali (Munich, DE)

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Machine learning reveals metabolic and inflammatory predictors of exercise adaptation in HFpEF

Speaker: Doctor J. Marino (Greifswald, DE)

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AI-enhanced risk prediction in acute heart failure: combining radiographic biomarkers with clinical data

Speaker: Assistant Professor K. Jeon (Seongnam, KR)

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Machine learning profiling of epicardial adipose tissue using multi-omics data from ventricular biopsies

Speaker: Mr A. Mircea (Lausanne, CH)

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From molecules to models: AI applications in omics and biomarkers

Speakers: Ms R. Tchala Sare, Mr J. Versnjak, Mr M. Ali, Doctor J. Marino, Assistant Professor K. Jeon...
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ESC Digital & AI Summit 2025

21 November - 22 November 2025

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