ESC Professional Premium Access

Enhancing the selection of heart failure patients for invasive procedures: how machine learning can predict the diagnostic yield of endomyocardial biopsy

Congress Presentation

About the speaker

Doctor Christian Basile

University of Naples Federico II, Naples (Italy)
1 presentation
1 follower

4 more presentations in this session

Development and validation of a predicting model for risk of rehospitalization within 30 days in heart failure patients with preserved ejection fraction

Speaker: Professor Y. Zhu (Xiangtan, CN)

Thumbnail

Machine learning to improve the performance of natriuretic peptides across age groups for the diagnosis of acute heart failure

Speaker: Mr D. Perez Vicencio (Edinburgh, GB)

Thumbnail

High prevalence of cardiotropic viruses in endomyocardial biopsies from patients with inflammatory cardiomyopathy demonstrated by a novel targeted NGS approach

Speaker: Doctor C. Baumeier (Berlin, DE)

Thumbnail

Predicting heart failure in cancer survivors: use of polygenic risk vs clinical score

Speaker: Doctor C. Soh (Melbourne, AU)

Thumbnail

Access the full session

Get out your crystal ball: predicting heart failure events using models

Speakers: Doctor C. Basile, Professor Y. Zhu, Mr D. Perez Vicencio, Doctor C. Baumeier, Doctor C. Soh
Thumbnail

About the event

Image

ESC Congress 2024

30 August - 2 September 2024

Sessions Presentations