Balcioglu, O.; Ozgocmen, C.; Ozsahin, D.U.; Yagdi, T. The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review. Diagnostics2024, 14, 380.
Balcioglu, O.; Ozgocmen, C.; Ozsahin, D.U.; Yagdi, T. The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review. Diagnostics 2024, 14, 380.
Balcioglu, O.; Ozgocmen, C.; Ozsahin, D.U.; Yagdi, T. The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review. Diagnostics2024, 14, 380.
Balcioglu, O.; Ozgocmen, C.; Ozsahin, D.U.; Yagdi, T. The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive Review. Diagnostics 2024, 14, 380.
Abstract
Especially in the last two decades, due to the developments in durable mechanical
circulatory support (MCS) technology and applications, left ventricular assist (LVAD) implantation has become used in more fragile end-stage heart failure patients with higher risk.
Despite advances in technology and patient care processes, right heart failure remains the leading cause of morbidity and mortality after durable LVAD implantation. It is difficult to make decisions about the type and duration of MCS during preoperative evaluation, and many clinical, hemodynamic, biochemical and echocardiographic criteria must be taken into account when evaluating the right ventricle.
Complex quantitative scoring systems, including measurements of different risk factors for postimplant right ventricular failure, and composite variables, including the anatomical and functional status of the right ventricle, have been used to decide between left or biventricular assist device implantation.
The successful use of artificial intelligence (AI) and machine learning (ML) in various applications in the medical field has paved the way for the idea of using it to better predict possible conditions such as right heart failure after LVAD implantation.
This review aims to evaluate the current situation of risk prediction models using AI and ML technology, which have become popular in recent years, and possible future developments in predicting right heart failure after the application of durable MCS systems.
Keywords
left ventricular assist device; right heart failure; right ventricle failure; artificial intelligence; machine learning
Subject
Medicine and Pharmacology, Cardiac and Cardiovascular Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
