prof. dr. M. Rienstra
Michiel Rienstra is a Clinical Cardiologist, Professor of Clinical Cardiology and Clinical Director at the University Medical Center Groningen, the Netherlands.
Graduated in medicine at the University of Antwerp, Belgium in 2003. Obtained a PhD at the University of Groningen, The Netherlands in 2007 on Atrial Fibrillation, Underlying Disease and Prognosis. I completed my cardiology training at the University Medical Center Groningen in 2012, where continued working as clinical cardiologist and researcher. I was awarded with a NWO Rubicon grant in 2009 and went to Harvard Medical School, Massachusetts General Hospital and the Framingham Heart Study for a post-doc on population genetics and epidemiology in 2010-2011. In 2012 I was awarded with the NWO Veni grant for my project on genetics of atrial fibrillation. In 2015 I received the European Society of Cardiology academic grant for his project on a big data approach in atrial fibrillation. I am work package leader of 4 large national consortia; RACE V (hypercoagulability and AF progression), RED-CVD (early detection of cardiovascular disease in general practices), AI (catalyzing the application of artificial intelligence in CV disease), and MyDigiTwin (Big-data and Artificial Intelligence-based ecosystem to create a user’s personal “Digital Twin”). I am steering committee member of several investigator-initiated clinical studies (RACE 2 to 7, MARC 1-2, VIP-HF, DECISION). I am fellow of the European Society of Cardiology and the American Heart Association, and Scientific & Clinical Education Lifelong Learning Committee (SCILL) member of the AHA - Genomics and Precision Medicine council.
I combine clinical cardiology focusing on treatment of patients with arrhythmias, with clinical-oriented research. My research consists of conducting clinical studies to improve AF treatment, studying epidemiology of AF and its risk factors in PREVEND, Lifelines and Framingham Heart Study, uncovering the genetics of atrial fibrillation in part with the international AFGen onsortium, and applying novel bioinformatics tools to improve AF risk prediction.
|Laatst gewijzigd:||20 september 2019 11:36|