Background

Egill received his MSc degree from Reykjavik University in Biomedical Engineering in 2012. Following that he worked for some years at the department of Clinical Engineering and IT as a project manager involved in the procurement and management of medical devices and information systems. After that he decided to pursue a PhD on the topic of modelling the effects of neuromodulation treatments for psychiatric disorders. The work was done at the department of Psychiatry at the Academic Medical Center in Amsterdam. He defended his thesis in November 2023 titled Modelling the Mind: Neuromodulation in psychiatric disorders.

Currently his interests lie in leveraging state of the art deep learning techniques such as self-supervised models, graph neural networks and transformers in the domain of large scale electronic medical records data. 

Publications

Fridgeirsson, E.A., Williams, R., Rijnbeek, P., Suchard M.A. & Reps, J.M. (2024) Comparing penalization methods for linear models on large observational health data. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocae109

C. Yang., Fridgeirsson E.A., Kors, J.A., Reps, J.M. & Rijnbeek P.R. (2024) Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. Journal of Big Data 11 (1), 7. https://doi.org/10.1186/s40537-023-00857-7

M. Schuemie, J. Reps., A. Black, F. DeFalco., Evans, L., Fridgeirsson, E., Gilbert, J.P., Knoll, C., ... and Suchard M., Health-Analytics Data to Evidence Suite (HADES): Open-Source Software for Observational Research. (2024). Studies in health technology and informatics. 310, 966. https://doi.org/10.3233/2FSHTI231108

Fridgeirsson, E.A., Sontag, D. & Rijnbeek, P. Attention-based neural networks for clinical prediction modelling on electronic health records. BMC Med Res Methodol 23, 285 (2023). https://doi.org/10.1186/s12874-023-02112-2

Seinen, T. M., Kors, J. A., van Mulligen, E. M., Fridgeirsson, E., & Rijnbeek, P. R. (2023). The added value of text from Dutch general practitioner notes in predictive modeling. Journal of the American Medical Informatics Association, ocad160. https://doi.org/10.1093/jamia/ocad160

Lee, D. Y., Choi, B., Kim, C., Fridgeirsson, E., Reps, J., Kim, M., ... & Park, R. W. (2023). Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study. Journal of medical Internet research, 25, e46165. https://doi.org/10.2196/46165

Fridgeirsson, E. A., Bais, M. N., Eijsker, N., Thomas, R. M., Smit, D. J., Bergfeld, I. O., ... & Denys, D. (2023). Patient specific intracranial neural signatures of obsessions and compulsions in the ventral striatum. Journal of neural engineering, 20(2), 026008. https://doi.org/10.1088/1741-2552/acbee1

Fridgeirsson, E. A., Bergfeld, I. O., de Kwaasteniet, B., Luigjes, J., van Laarhoven, J., Notten, P., ... & van Wingen, G. (2023). Deep brain stimulation modulates directional limbic connectivity in major depressive disorder. medRxiv, 2023-05. https://doi.org/10.1101/2023.05.18.23290168

John, L. H., Kors, J. A., Fridgeirsson, E. A., Reps, J. M., & Rijnbeek, P. R. (2022). External validation of existing dementia prediction models on observational health data. BMC Medical Research Methodology, 22(1), 1-12. https://doi.org/10.1186/s12874-022-01793-5

Seinen, T. M., Fridgeirsson, E. A., Ioannou, S., Jeannetot, D., John, L. H., Kors, J. A., ... & Rijnbeek, P. R. (2022). Use of unstructured text in prognostic clinical prediction models: a systematic review. Journal of the American Medical Informatics Association, 29(7), 1292-1302. https://doi.org/10.1093/jamia/ocac058

Xiaoyu Chen, Zhen Wang, Qian Lv, Qiming Lv, Guido van Wingen, Egill Axfjord Fridgeirsson, Damiaan Denys, Valerie Voon, Zheng Wang. Common and differential connectivity profiles of deep brain stimulation and capsulotomy in refractory obsessive-compulsive disorder. Molecular Psychiatry. 2022. https://doi.org/10.1038/s41380-021-01358-w

Tom M Seinen, Egill A Fridgeirsson, Solomon Ioannou, Daniel Jeannetot, Luis H John, Jan A Kors, Aniek F Markus, Victor Pera, Alexandros Rekkas, Ross D Williams, Cynthia Yang, Erik M van Mulligen, Peter R Rijnbeek. Use of unstructured text in prognostic clinical prediction models: a systematic review. Journal of the American Medical Informatics Association. 2022. https://doi.org/10.1093/jamia/ocac058

Ottenhoff, M.C., Ramos, L.A., Potters, W., Janssen, M.LF., Hubers, D., Pina-Fuentes, D. [et al including E.A. Fridgeirsson] Predicting mortality of individual COVID-19 patients: A multicenter Dutch cohort. BMJ open. 2021. https://doi.org/10.1101/2020.10.10.20210591

Fridgeirsson, E.A., Deng, Z.D., Denys, D., van Waarde, J., van Wingen, G.  Electric field strength induced by electroconvulsive therapy is associated with clinical outcome.  Neuroimage Clinical. 2021. https://doi.org/10.1016/j.nicl.2021.102581

Fridgeirsson, E. A., Figee, M., Luigjes, J., van den Munckhof, P., Richard Schuurman, P., van Wingen, G., & Denys, D. Deep brain stimulation modulates directional limbic connectivity in obsessive-compulsive disorder. Brain. 2020. https://doi.org/10.1093/brain/awaa100

Bruin, W. B., Taylor, L., Thomas, R. M., Shock, J. P., Zhutovsky, P., Abe, Y., [et al including E.A. Fridgeirsson] Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters. Translational Psychiatry. 2020. https://doi.org/10.1038/s41398-020-01013-y

Boedhoe, P. S. W., van Rooij, D., Hoogman, M., Twisk, J. W. R., Schmaal, L., Abe, Y., [et al including E.A. Fridgeirsson] Subcortical brain volume, regional cortical thickness, and cortical surface are a across disorders: findings from the ENIGMA ADHD, ASD and OCD working groups. American Journal of Psychiatry. 2020. https://doi.org/10.1176/appi.ajp.2020.19030331

Kong, X. Z., Boedhoe, P. S. W., Abe, Y., Alonso, P., Ameis, S. H., Arnold, P. D., [et al including E.A. Fridgeirsson] Mapping cortical and subcortial asymmetry in obsessive-compulsive disorder: findings from the ENIGMA consortium. Biological Psychiatry. 2020. https://doi.org/10.1016/j.biopsych.2019.04.022

Boedhoe, P. S. W., Heymans, M. W., Schmaal, L., Abe, Y., Alonso, P., [et al including E.A. Fridgeirsson] An empirical comparison of meta- and mega-analysis with data from the ENIGMA obsessive-compulsive disorder working group. Frontiers in neuroinformatics 2019. https://doi.org/10.3389/fninf.2018.00102

Boedhoe, P. S. W., Schmaal, L., Abe, Y., Alonso, P., Ameis, S. H., Anticevic, A., [et al including E.A. Fridgeirsson] Cortical abnormalities associated with pediatric and adult obsessive-compulsive disorder: findings from the ENIGMA Obsessive-Compulsive Disorder Working Group. American Journal of Psychiatry. 2018. https://doi.org/10.1176/appi.ajp.2017.17050485

Gargiulo, P., Belfiore, P., Fridgeirsson, E. A., Vanhatalo, S., & Ramon, C. The effect of fontanel on scalp EEG potentials in the neonate. Clinical Neurophysiology. 2015. https://doi.org/10.1016/j.clinph.2014.12.002 

Ramon, C., Garguilo, P., Fridgeirsson, E. A., & Haueisen, J. Changes in scalp potentials and spatial smoothing effects of inclusion of dura layer in human head models for EEG simulations. Frontiers in Neuroengineering. 2014. https://doi.org/10.3389/fneng.2014.00032 

Egill A Fridgeirsson, Paolo Gargiulo, Ceon Ramon, Jens Haueisen. 3D segmented model of head for modelling electrical activity of the brain. European Journal of Translational Myology. 2012. https://doi.org/10.4081/ejtm.2012.1793 

Book chapters 

Deng, Z.D., Liston, C., Gunning, F.M., Dubin, M.J.,Fridgeirsson, E.A., Lilien, J., van Wingen, G., van Waarde, J. Electrical Field Modelling for Transcranial Magnetic Stimulation and Electroconvulsive Therapy. Brain and Human Body Modelling. 2019. https://doi.org/10.1007/978-3-030-21293-3_4  

Conference Papers 

Markus, A. F., Fridgeirsson, E. A., Kors, J. A., Verhamme, K. M., Reps, J. M., & Rijnbeek, P. R. (2023, July). Understanding the Size of the Feature Importance Disagreement Problem in Real-World Data. In ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH).

Yang, C., Fridgeirsson, E. A., Kors, J. A., Reps, J. M., Rijnbeek, P. R., Wong, J., & Williams, R. D. (2023). Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability?. CARING IS SHARING–EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION, 129.

Markus, A. F., Fridgeirsson, E. A., Kors, J. A., Verhamme, K. M., & Rijnbeek, P. R. (2023). Challenges of Estimating Global Feature Importance in Real-World Health Care Data. CARING IS SHARING–EXPLOITING THE VALUE IN DATA FOR HEALTH AND INNOVATION, 1057.

D Denys, EA Fridgeirsson, N Eijsker, MN Bais, RM Thomas, IO Bergfeld, PR Schuurman, P van den Munckhof, P de Koning, M Figee. Concurrent Intracranial and Extracranial Electrophysiological Recordings in Humans: relevance for deep brain stimulation in psychiatric disorders. Brain Stimulation: Basic, Translational, and Clinical Research in Neuromodulation. 2022

Hu, S., Fridgeirsson, E.A., van Wingen, G., Welling, M., Transformer-based Deep Survival Analysis. AAAI spring symposium on Survival Prediction. 2020.