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- W4386774666 abstract "Several artificial intelligence (AI) and machine learning (ML) algorithms have been constructed for cardiovascular medicine applications. These models have the potential to positively augment decision-making at the detection, management, and transplantation stages, thereby enhancing personalization, efficiency, and outcomes. However, concerns regarding generalizability, interoperability, and interpretability hinder their adoption in the clinical setting. In this chapter, recent AI/ML developments for heart failure and cardiomyopathy are discussed. This discussion is contextualized to the basic principles of AI/ML, and relevant areas of emerging research are identified. The primary objective is to highlight the vast potential of these intelligent systems, yet also outline limitations that must be addressed prior to implementation. Although AI/ML algorithms offer a multitude of benefits for decision-making in heart failure and cardiomyopathy, they are not ready to be utilized autonomously. Instead, iterative refinement must take place to allow for their effective integration as decision-support tools for cardiovascular applications." @default.
- W4386774666 created "2023-09-16" @default.
- W4386774666 creator A5035023430 @default.
- W4386774666 creator A5092177968 @default.
- W4386774666 date "2024-01-01" @default.
- W4386774666 modified "2023-09-27" @default.
- W4386774666 title "Artificial intelligence in heart failure and transplant" @default.
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- W4386774666 doi "https://doi.org/10.1016/b978-0-443-15688-5.00036-x" @default.
- W4386774666 hasPublicationYear "2024" @default.
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