AI Medical Compendium Journal:
Future cardiology

Showing 1 to 8 of 8 articles

Generalization challenges in electrocardiogram deep learning: insights from dataset characteristics and attention mechanism.

Future cardiology
Deep learning's widespread use prompts heightened scrutiny, particularly in the biomedical fields, with a specific focus on model generalizability. This study delves into the influence of training data characteristics on the generalization performan...

Cardiology in the digital era: from artificial intelligence to Metaverse, paving the way for future advancements.

Future cardiology
Tweetable abstract Cardiology's digital revolution: AI diagnoses, ChatGPT consults, Metaverse educates. Challenges & promises explored. #CardiologyTech #DigitalHealth.

Harnessing artificial intelligence in cardiac rehabilitation, a systematic review.

Future cardiology
This systematic review aims to evaluate the current body of research surrounding the efficacy of artificial intelligence (AI) in cardiac rehabilitation. Presently, AI can be incorporated into personal devices such as smart watches and smartphones, i...

Potential of machine learning methods to identify patients with nonvalvular atrial fibrillation.

Future cardiology
Nonvalvular atrial fibrillation (NVAF) is associated with an increased risk of stroke however many patients are diagnosed after onset. This study assessed the potential of machine-learning algorithms to detect NVAF. A retrospective database study u...

AI-based prediction of left bundle branch block risk post-TAVI using pre-implantation clinical parameters.

Future cardiology
BACKGROUND AND AIMS: Transcatheter Aortic Valve Implantation (TAVI) has revolutionized the treatment of severe aortic stenosis. Although its clinical efficacy is well established, the development of new-onset left bundle branch block (LBBB) following...