Coronary artery disease (CAD), constitute the leading causes of death in developed countries. This project aims to implement state-of-the-art machine learning -based artificial intelligence analytics on diverse data to improve diagnosis and prediction of cardiovascular outcomes. The first objective is to generate an adaptive and self-sustaining workflow for the collection, storage, integration, analysis and continuous update of available patient clinical, imaging and genetic cardiovascular data in Finland and Netherlands. The second objective is to incorporate, train and validate a range of statistical machine learning algorithms on the aforementioned data in order to offer support estimations both in the diagnosis and outcome prediction of patients with known or suspected CAD. This can be expected to increase the accuracy of diagnostics and predictive power of available data allowing highly individualized risk-based therapy guidance.

2022

2026