Area of research
Cardiology and Cardiovascular Medicine · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Cardiac Imaging and Diagnostics, Artificial Intelligence in Healthcare and Education, Machine Learning in Healthcare, and Cardiovascular Function and Risk Factors.
Detecting structural heart disease from electrocardiograms using AI
Rethinking clinical trials for medical AI with dynamic deployments of adaptive systems
Deep learning for echocardiographic assessment and risk stratification of aortic, mitral, and tricuspid regurgitation: the DELINEATE-regurgitation study
International partnership for governing generative artificial intelligence models in medicine
Artificial Intelligence for Cardiovascular Care—Part 1: Advances
Artificial Intelligence in Cardiovascular Care—Part 2: Applications
Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR)
Implications of Bias in Artificial Intelligence: Considerations for Cardiovascular Imaging
Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging
Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry