Focus on Artificial IntelligenceMachine Learning Prediction Models for In-Hospital Mortality After Transcatheter Aortic Valve Replacement
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Key Words
machine learning
mortality
transcatheter aortic valve replacement
Abbreviations and Acronyms
ACC
American College of Cardiology
AI
artificial intelligence
ANN
artificial neural networks
AUC
area under the receiver-operating curve
CI
confidence interval
ICD-9-CM
International Classification of Diseases-9th Edition-Clinical Modification
LR
logistic regression
ML
machine learning
NB
naive Bayes
NIS
National Inpatient Sample
RF
random forest
SAVR
surgical aortic valve replacement
STS
Society of Thoracic Surgeons
TAVR
transcatheter aortic valve replacement
TVT
transcatheter valve therapy
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This study was funded by the National Institutes of Health (U54MD007587, U54MD007600, S21MD001830, R25MD007607, and TL1TR001434-3). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. Dr. Pinto serves as a consultant for Medtronic, Abbott Vascular, Abiomed, NuPulse, Siemens, and Boston Scientific. Dr. Latib has served on the advisory boards of Medtronic and Abbott Vascular. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
© 2019 by the American College of Cardiology Foundation. Published by Elsevier.