Machine learning based risk stratification of patients undergoing cardiac resynchronization therapy

Back

HFA Premium Access

Machine learning based risk stratification of patients undergoing cardiac resynchronization therapy

Session: Rapid Fire 6 - Risk stratification and prognosis

Topic: Cardiac Resynchronisation Therapy (CRT)

Speaker: Doctor M. Tokodi (Budapest, HU)

Event: Heart Failure 2019

Congress Presentation

Add to my library

About the speaker

Doctor Marton Tokodi

Semmelweis University, Budapest (Hungary)

1 presentation

0 follower

14 more presentations in this session

Prognostic impact of ICD interventions in a real-world primary and secondary prevention population

Speaker: Assistant Professor M. Canepa (Genoa, IT)

Predicting arrhythmic risk in dilated cardiomyopathy: a meta-analysis of clinical parameter

Speaker: Doctor A. Sammani (Utrecht, NL)

Serial change of Layer-specific myocardial functionby Chemotherapy in Breast cancer patients

Speaker: Doctor M. Kim (Seoul, KR)

Forecast of mOrtality Risk Early in the postCardiac Arrest Syndrome Therapy: pilot score for estimate early mortality in post cardiac arrest syndrome patient population

Speaker: Associate Professor E. Zima (Budapest, HU)

Early heart remodeling in type 1 diabetes patients: possible phenotypes

Speaker: Miss N. Safarova (Hagen, DE)

Access the full session

Rapid Fire 6 - Risk stratification and prognosis

Speakers: Doctor M. Tokodi, Assistant Professor M. Canepa, Doctor A. Sammani, Doctor M. Kim, Associate Professor E. Zima...

Access

About the event

Heart Failure 2019

25 May - 28 May 2019

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources