FA
Folkert W. Asselbergs
Amsterdam University Medical Centers, University College London, University Medical Center Utrecht
Research areas: Medicine · Cardiology and Cardiovascular Medicine · Genetic Associations and Epidemiology · Cardiomyopathy and Myosin Studies · Cardiac electrophysiology and arrhythmias
0000-0002-1692-8669
Employment
- 2022 - Present
-
Universitair Medisch Centrum Utrecht Consultant Cardiologist2010 - 2022
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (1392)
- Personalized Remote Patient Management in Heart Failure Save
- Resistant Hypertension Variants Link to Hyperaldosteronism and Potassium Levels Save
- The Dutch cardiomyopathy registry (DCR); rationale and registry design Save
- Sport Type Alone Does Not Reliably Predict Distinct Cardiac Phenotypes in Athletes. Save
- 2026 ESC Guidelines for the management of cardiovascular disease and chronic kidney disease, in collaboration with the European Renal Association (ERA) Save
- 2026 ESC Guidelines for the management of heart failure. Save
- 2026 ESC Guidelines on cardiac rehabilitation. Save
- Strategic Patient Involvement in Medical AI Co-Design: A Pilot Study in Heart Failure Save
- The Need for Fully-Effective Federated Analytics of Data Sources for Clinical Trials Save
- Risk factors and coronary events: attenuation of the association in secondary prevention Save
- Cardiology hospital admission risk prediction: training, internal validation and technical implementation in the electronic health record Save
- External validation of models predicting heart failure in haematological malignancies Save
- Pathophysiological analysis of serially measured plasma biomarkers, remote monitoring and clinical events, in symptomatic patients with moderate to severe chronic heart failure Save
- Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction Save
- Contrastive explainable AI in healthcare: a systematic review of trends, benefits, research gaps, and future directions. Save
- Real-time prediction of atrial fibrillation in intensive care unit: a meta-learning approach Save
- Big Data and Trustworthy AI for Heart Failure: A Review Save
- Perceived responsibility and willingness to engage in self-care among heart failure patients Save
- Generating evidence using electronic alerts during routine care: a fully automated randomised controlled trial of oral fluid restriction in acute heart failure (THIRST Alert Trial) Save
- Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction Save