Outcome Analysis in Elective Electrical Cardioversion of Atrial Fibrillation Patients: Development and Validation of a Machine Learning Prognostic Model.

Jean C Nuñez-Garcia Antonio Sánchez-PuenteJesús Sampedro-GómezVictor Vicente-PalaciosManuel F Jiménez-NavarroArmando Oterino-ManzanasJavier Jiménez-CandilPedro-Ignacio Dorado-Díaz Pedro Luis Sánchez

Published in: Journal of clinical medicine (2022)

An ML model improves the accuracy of restoring and maintaining SR predictions over current discriminators. The proposed approach enables a detailed simulation of the patient flow through personalized predictions.

Keyphrases

atrial fibrillation
machine learning
end stage renal disease
ejection fraction
newly diagnosed
chronic kidney disease
heart failure
patients undergoing
prognostic factors
case report
catheter ablation
left atrial
deep learning
direct oral anticoagulants
mitral valve
virtual reality