Unlocking the potential of Artificial Intelligence in Sports Cardiology: does it have a role in evaluating athlete's heart?
Stefano PalermiMarco VecchiatoAndrea SagliettoDavid NiederseerDavid Lee OxboroughSandra Ortega-MartorellIvan OlierSilvia CastellettiAaron BaggishFrancesco MaffessantiAlessandro BiffiAntonello D'AndreaAlessandro ZorziElena CavarrettaFlavio D'AscenziPublished in: European journal of preventive cardiology (2024)
The integration of artificial intelligence (AI) technologies is evolving in different fields of cardiology and in particular in sports cardiology. AI offers significant opportunities to enhance risk assessment, diagnosis, treatment planning, and monitoring of athletes. This article explores the application of AI in various aspects of sports cardiology, including imaging techniques, genetic testing and wearable devices. The use of machine learning and deep neural networks enables improved analysis and interpretation of complex data sets. However, ethical and legal dilemmas must be addressed, including informed consent, algorithmic fairness, data privacy, and intellectual property issues. The integration of AI technologies should complement the expertise of physicians, allowing for a balanced approach that optimizes patient care and outcomes. Ongoing research and collaborations are vital to harness the full potential of AI in sports cardiology and advance our management of cardiovascular health in athletes.
Keyphrases
- artificial intelligence
- big data
- machine learning
- deep learning
- thoracic surgery
- cardiac surgery
- risk assessment
- neural network
- high school
- human health
- heart failure
- high resolution
- electronic health record
- metabolic syndrome
- acute kidney injury
- adipose tissue
- data analysis
- atrial fibrillation
- heavy metals
- health information
- insulin resistance
- social media