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Non-traditional risk factors and artificial intelligence in the management of atrial fibrillation
doi : 10.1093/eurheartj/ehaf028
Volume 46, Issue 9, 1 March 2025
Artificial intelligence in patients with atrial fibrillation to manage clinical complexity and comorbidities: the ARISTOTELES project
Shaping the future of cardiovascular research: a focus on cardioimmunology
European Research Council-funded grant: programming the epicardium to cure broken hearts
Non-traditional risk factors for atrial fibrillation: epidemiology, mechanisms, and strategies
Artificial intelligence and digital tools for design and execution of cardiovascular clinical trials
Mechanism of syncope: role of ambulatory blood pressure monitoring and cardiovascular autonomic function assessment
24-hour ambulatory blood pressure monitoring: a game changer in the management of reflex syncope?
Artificial intelligence–derived electrocardiographic aging and risk of atrial fibrillation: a multi-national study
AI-ECG and prediction of new atrial fibrillation: when the heart tells the age
Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease
Expanding artificial intelligence to understudied populations: congenital heart disease as the next frontier
Rate dependent complete right bundle block: a challenging diagnosis in Brugada syndrome
Weekly Journal Scan: The jury is still out on beta-blockers following acute myocardial infarction with preserved ejection fraction after the ABYSS trial
Correction to: Obesity and cardiovascular disease: an ESC clinical consensus statement
