Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes-Reference-Cited by-同舟云学术

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes

Published:2018-01 Issue:1 Volume:11 Page:
ISSN:1941-3149
Container-title:Circulation: Arrhythmia and Electrophysiology
language:en
Short-container-title:Circ Arrhythm Electrophysiol

Author:

Kalscheur Matthew M.¹,Kipp Ryan T.¹,Tattersall Matthew C.¹,Mei Chaoqun¹,Buhr Kevin A.¹,DeMets David L.¹,Field Michael E.¹,Eckhardt Lee L.¹,Page C. David¹

Affiliation:

1. From the Division of Cardiovascular Medicine, Department of Medicine, School of Medicine and Public Health (M.M.K., R.T.K., M.C.T., M.E.F., L.L.E.), Department of Biostatistics and Medical Informatics (C.M., K.A.B., D.L.D., C.D.P.), University of Wisconsin Institute for Clinical and Translational Research (C.M.), and Department of Computer Sciences (C.D.P.), University of Wisconsin-Madison.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

Reference45 articles.

1. Cardiac-Resynchronization Therapy with or without an Implantable Defibrillator in Advanced Chronic Heart Failure

2. The Effect of Cardiac Resynchronization on Morbidity and Mortality in Heart Failure

3. Cardiac-Resynchronization Therapy for the Prevention of Heart-Failure Events

4. Cardiac-Resynchronization Therapy for Mild-to-Moderate Heart Failure

5. Randomized Trial of Cardiac Resynchronization in Mildly Symptomatic Heart Failure Patients and in Asymptomatic Patients With Left Ventricular Dysfunction and Previous Heart Failure Symptoms

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