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UNSUPERVISED MACHINE LEARNING ALGORITHM TO IDENTIFY HIGH AND LOW RISK PATIENTS FOLLOWING CRT IMPLANTATION

Authors :
W R Schwertner
Annamaria Kosztin
Béla Merkely
Márton Tokodi
Bálint Károly Lakatos
Péter Perge
Attila Kovács
Sirish Shrestha
Source :
Journal of the American College of Cardiology. 71:A947
Publication Year :
2018
Publisher :
Elsevier BV, 2018.

Abstract

Cardiac Resynchronization Therapy (CRT) is an effective treatment of chronic heart failure (HF) in patients with wide QRS and reduced ejection fraction. However, not every patient benefits equally from the treatment and still high mortality rates can be observed. Our aim was to identify patients

Details

ISSN :
07351097
Volume :
71
Database :
OpenAIRE
Journal :
Journal of the American College of Cardiology
Accession number :
edsair.doi...........140ce6b5c54782ba0b3cced5b693ebfa