Back

Derivation and validation of a machine learning-based risk prediction model for in-hospital mortality in patients with acute heart failure.

29 August 2022 (17:15 - 18:00)
Organised by:
Congress Presentation Part of: Acute heart failure - Biomarkers Biomarkers ESC Professional Premium Access ESC Congress 2022

About the speaker

Photo
Doctor Kayo Misumi

Kyushu University Faculty of Medical Sciences, Fukuoka (Japan)

7 More presentations in this session

Presentation thumbnail
Remote dielectric sensing detects pulmonary congestion in emergency patients with dyspnoea
Doctor A. Olesen (Copenhagen, DK)
Abstract Slides
Presentation thumbnail
Relation of lymphopenia to comorbidity burden and its prognostic value in patients with acute decompensated heart failure with preserved left ventricular ejection fraction: a multicentre study
Mr S. Tamaki (Toon, JP)
Abstract Slides
Presentation thumbnail
Relationship between GDF-15, urinary sodium and markers of renal function in patients with chronic heart failure
Doctor G. Moreira (Niteroi, BR)
Abstract Slides
Presentation thumbnail
Characterization and prognostic relevance of neuron specific enolase (NSE) after cardiopulmonary resuscitation (CPR) with extracorporeal circulation (e - CPR)
Doctor F. Haertel (Jena, DE)
Abstract Slides
Presentation thumbnail
Tissue inhibitor of metalloproteinase (TIMP)-1 predicts negative remodeling and recovery of ejection fraction in acute heart failure with reduced ejection fraction.
Doctor C. Tseng (Taipei, TW)
Abstract Slides

Access the full session

Session thumbnail
Acute heart failure - Biomarkers

The Event

Event poster

ESC Congress 2022

29 August 2022 17:15 CET
You may be interested in
thumbnail
Congress Presentation
State-of-the-art lecture on current state of the diagnosis of heart failure
thumbnail
Congress Presentation
The role of a multimarker panel in the diagnosis and prognosis of patients with acute heart failure
thumbnail
Congress Session
From genetic signatures to clinical implications

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources