Ilias Nikolakopoulos, MD

Ilias is a resident at the Internal Medicine Program at Yale. Prior to residency, he was a research fellow at the Minneapolis Heart Institute Center for Coronary Artery and worked on multicenter registries and randomized controlled trials on topics spanning complex high-risk indicated cardiac procedures, myocardial infarction, and stress cardiomyopathy. Several of his projects used imaging to guide procedures, and that is what made him interested in cardiac imaging as well. During this time, he also grew an interest in methodology and data analysis, incorporating methods such as Bayesian statistics into his projects.

During residency, he continues to work on noninvasive imaging for cardiac risk stratification and risk stratification before percutaneous coronary interventions. He continues to expand on his interests in observational data analysis, currently focusing on machine learning clustering models as well as the assessment of the predictive ability of time-to-event models. He also gained experience in the regulatory side of research, serving at the Yale IRB. Ilias is interested in applying methods for observational causal inference and prediction to data derived from EHR and noninvasive cardiac imaging with the goal of personalizing the diagnosis and treatment of coronary artery disease.

His work has been published in several peer-reviewed journals, including Circulation, JACC Cardiovascular Interventions, Circulation Cardiovascular Interventions, Catheterization and Cardiovascular Interventions, International Journal of Cardiology, American Journal of Cardiology, Eurointervention.