Machine Meets Biology: a Primer on Artificial Intelligence in Cardiology and Cardiac Imaging

AbstractPurpose of ReviewAn understanding of the basics concepts of deep learning can be helpful in not only understanding the potential applications of this technique but also in critically reviewing literature in which neural networks are utilized for analysis and modeling.Recent FindingsThe term “deep learning” has been applied to a subset of machine learning that utilizes a “neural network” and is often used interchangeably with “artificial intelligence.” It has been increasingly utilized in healthcare for computational “learning”, especially for pattern recognition for dia gnostic imaging. Another promising application is the potential for these neural networks to improve the accuracy in the identification of patients who are at risk for cardiovascular events and could benefit most from preventive treatment in comparison with more conventional statistical techniques. The importance of such tailored cardiovascular risk assessment and disease management in individual patients is far reaching given that cardiovascular disease is the leading cause of morbidity and mortality in the world. Nearly half of myocardial infarctions and strokes occur in patients who are not predicted to be at risk for cardiovascular events by current guideline-based approaches. Equally important are individuals who are not at risk for cardiovascular events and yet are given expensive and unnecessary preventive treatment with potential untoward side effects.SummaryThe application of p...

Source: Current Cardiology Reports - October 18, 2018 Category: Cardiology Source Type: research