An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation

An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation

<i>Background</i>: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. <i>Aim</i>: This study a...

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Main Authors: Abilkhair Kurmanaliyev, Kristina Sutiene, Rima Braukylienė, Ali Aldujeli, Martynas Jurenas, Rugile Kregzdyte, Laurynas Braukyla, Rassul Zhumagaliyev, Serik Aitaliyev, Nurlan Zhanabayev, Rauan Botabayeva, Yerlan Orazymbetov, Ramunas Unikas
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Medicina
Subjects:
aortic stenosis
transcatheter aortic valve implantation
early safety outcomes
ADASYN
random forest
SHAP
Online Access:https://www.mdpi.com/1648-9144/61/3/374
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