What is it about?
We have created and deployed a transparent method that allows for personalized medical treatment to prevent atrial fibrillation episodes after cardiac surgery. Our method finds medical descriptions of patients (e.g. AGE > 65 and BLOOD LOSS > 1500) that describe a patient that has been found to have a higher risk of developing atrial fibrillation after surgery. Known and unknown medical descriptions were detected, and several of them are included in future research at the collaborating hospital.
Featured Image
Photo by Joshua Chehov on Unsplash
Why is it important?
With our method, the hospital can give medication to high risk patients before they undergo cardiac surgery. This would decrease the cases of atrial fibrillation episodes and thereby decrease the number of negative effects of such an episode (such as blood clots and strokes).
Perspectives
This collaboration with the hospital has been the perfect way of applying the knowledge gained throughout my studies for good. It is inspiring to work with real-life medical data and it feels like a privilege to have gotten the trust of the hospital to work with this. All in all, I have enjoyed this collaboration a lot and I am looking forward to future collaborations and projects.
Lieke van den Biggelaar
Technische Universiteit Eindhoven
Read the Original
This page is a summary of: Characterizing the Risk of Atrial Fibrillation in Cardiac Patients with Exceptional Electrocardiogram Phenotypes, August 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3711896.3737200.
You can read the full text:
Contributors
The following have contributed to this page
