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UNSUPERVISED MACHINE LEARNING ALGORITHM TO IDENTIFY HIGH AND LOW RISK PATIENTS FOLLOWING CRT IMPLANTATION
- 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
- Subjects :
- medicine.medical_specialty
Ejection fraction
business.industry
medicine.medical_treatment
High mortality
Cardiac resynchronization therapy
medicine.disease
QRS complex
Internal medicine
Heart failure
cardiovascular system
Cardiology
Medicine
Unsupervised learning
Effective treatment
In patient
Cardiology and Cardiovascular Medicine
business
Subjects
Details
- ISSN :
- 07351097
- Volume :
- 71
- Database :
- OpenAIRE
- Journal :
- Journal of the American College of Cardiology
- Accession number :
- edsair.doi...........140ce6b5c54782ba0b3cced5b693ebfa