Back

Identification of machine learning-derived survival clusters in patients hospitalized for acute decompensated heart failure, in the overall population and stratified by sex

17 May 2025 (10:00 - 10:45)
Organised by: Logo
Congress Presentation Part of: Acute heart failure epidemiology Epidemiology, Prognosis, Outcome HFA Premium Access Heart Failure 2025 Heart Failure Association (HFA)

About the speaker

Photo
Doctor Stefano Contessi

Hospital Santa Maria della Misericordia, Udine (Italy)

5 More presentations in this session

Presentation thumbnail
Takotsubo syndrome in the 21st century: a portuguese picture from a tertiary center
Doctor M. Presume (Lisbon, PT) Doctor R. Carvalho (Lisbon, PT)
Abstract Slides Video
Presentation thumbnail
Advancements and challenges in acute heart failure management in Korea: initial report and insights from the Korean heart failure III registry
Professor H. Cho (Seoul, KR)
Abstract Slides Video
Presentation thumbnail
Differences in clinical presentation and outcomes between de novo heart failure and acute decompensated chronic heart failure: a retrospective observational study.
Doctor C. Cardile (Rome, IT)
Abstract Slides Video
Presentation thumbnail
Identifying cardiogenic shock sub-phenotypes with machine learning: a multicenter study combining clinical and echocardiographic data
Doctor A. Stefanini (Siena, IT)
Abstract Slides Video
Presentation thumbnail
Epidemiology, evolution and in-hospital outcome of STEMI patients presenting with acute heart failure
Doctor R. Filipescu (Bucharest, RO)
Abstract Slides Video

Access the full session

Session thumbnail
Acute heart failure epidemiology

The Event

Event poster

Heart Failure 2025

17 May 2025 10:00 CET
You may be interested in
thumbnail
Congress Session
Nursing and Allied Professions Investigator Award
thumbnail
Congress Presentation
Machine learning-derived phenotypes in heart failure with reduced ejection fraction: clinical implications beyond LVEF
thumbnail
Congress Presentation
Machine learning approach to identify phenotypes in patients with ischemic heart failure with reduced ejection fraction

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources