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Research interests

My research focusses on the bioinformatic analysis of high dimensional data (such as genetic data and imaging data) by applying various statistical and machine learning methods to gain better understanding of complex and multifactorial cardiovascular diseases.

My ongoing projects include identification of new markers for cardiovascular diseases and related traits as well as construction of processing and analysis pipelines for cardiac imaging data from large scale population cohorts.

Besides research activities, I currently serve on the board of Regional Student Group (RSG) Netherlands of the International Society of Computational Biology (ISCB) and on student committee for the organization of the new Summer School ‘Data Science and AI in Health’ offered by the University Medical Centre Groningen (UMCG) in 2021.

Publicaties

Genomic insights into cardiovascular traits from deep phenotyping of large-scale population cohorts

Fetuin-A and its genetic association with cardiometabolic disease

Hybridizing machine learning in survival analysis of cardiac PET/CT imaging

Machine learning in practice-Evaluation of clinical value, guidelines

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model

Artificial intelligence for the vasculome

Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies

Genomic insights in ascending aortic size and distensibility

Hybrid Cardiac Imaging: The Role of Machine Learning and Artificial Intelligence

Improving explainability of deep neural network-based electrocardiogram interpretation using variational auto-encoders

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