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

Session: From molecules to models: AI applications in omics and biomarkers
Topic: Machine Learning
Speaker: Mr A. Mircea (Lausanne, CH)
Event: ESC Digital & AI Summit 2025

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Mr Andrei-Alexandru Mircea

University Hospital Centre Vaudois (CHUV), Lausanne (Switzerland)
2 presentations
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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-based identification of patient clusters with distinct cardiac chronotropic responses during exercise

Speaker: Ms R. Tchala Sare (Paris, FR)

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From molecules to models: AI applications in omics and biomarkers

Speakers: Mr A. Mircea, Mr J. Versnjak, Mr M. Ali, Doctor J. Marino, Assistant Professor K. Jeon...
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About the event

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ESC Digital & AI Summit 2025

21 November - 22 November 2025

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