Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial

Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study sought to use a machine learning algorithm to develop a model to...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Circulation. Arrhythmia and electrophysiology Ročník 11; číslo 1; s. e005499
Hlavní autori:	Kalscheur, Matthew M, Kipp, Ryan T, Tattersall, Matthew C, Mei, Chaoqun, Buhr, Kevin A, DeMets, David L, Field, Michael E, Eckhardt, Lee L, Page, C David
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.01.2018
Predmet:	Aged Algorithms Cardiac Resynchronization Therapy - methods Decision Making Deep Learning Female Heart Conduction System - physiopathology Heart Failure - physiopathology Heart Failure - therapy Humans Machine Learning Male Middle Aged Predictive Value of Tests Stroke Volume - physiology Ventricular Function, Left - physiology algorithms heart failure hospitalization machine learning cardiac resynchronization therapy
ISSN:	1941-3084, 1941-3084
On-line prístup:	Zistit podrobnosti o prístupe
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!