2024
- Goules, A. V. et al (2024) Identification and evolution of predictors of Sjögren's disease-associated mucosa-associated lymphoid tissue lymphoma development over time: a case-control study. The Lancet Rheumatology
- Papagiannopoulos, O. D., Pezoulas, V. C., Papaloukas, C. & Fotiadis, D. I. (2024) 3D clustering of gene expression data from systemic autoinflammatory diseases using self-organizing maps (Clust3D). Computational and Structural Biotechnology Journal 23, 2152-2162.
- Koloi, A. et al. (2024) Predicting early-stage coronary artery disease using machine learning and routine clinical biomarkers improved by augmented virtual data. European Heart Journal-Digital Health ztae049.
- Pezoulas, V. C. et al. (2024) Synthetic data generation methods in healthcare: A review on open-source tools and methods. Computational and Structural Biotechnology Journal
- Zaridis, D. I. et al. (2024) ResQu-Net: Effective prostate’s peripheral zone segmentation leveraging the representational power of attention-based mechanisms. Biomedical Signal Processing and Control 93 106187.
- Lopez-Perez, L. et al. (2024) Statistical and machine learning methods for cancer research and clinical practice: A systematic review. Biomedical Signal Processing and Control 92, 106067.
- Zaridis, D. I. et al. (2024) ProLesA-Net: A multi-channel 3D architecture for prostate MRI lesion segmentation with multi-scale channel and spatial attentions. Patterns
- Pezoulas, V. C. et al. (2024) FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets. Patterns 5
2023
- O. Papagiannopoulos, K. Kourou, C. Papaloukas, ImmunAID Consortium, D.I. Fotiadis (2023) “Classification of Inflammation of Unknown Origin patients based on RNA-seq and SomaScan data” 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)
- A. Koloi, V. Loukas, A. Sakellarios, J. Bosch, R. Quax, K. Nowakowska, J. Kamierski, C. Papaloukas, D.I. Fotiadis (2023) “A comparison study on creating simulated patient data for individuals suffering from chronic coronary disorders 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)
- O.D. Papagiannopoulos, C. Papaloukas, D.I. Fotiadis (2023) “Deep Learning for Biomarkers Discovery in Auto-inflammatory Disorders” IEEE EMBS International Conference on Data Science and Engineering in Healthcare
2022
- O. Papagiannopoulos, K. Kourou, C. Papaloukas, D.I. Fotiadis (2022) “Comparison of High-Throughput Technologies in the Classification of Adult-Onset Still’s Disease Patients” 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- V.C. Pezoulas, A. Liontos, E. Mylona, C. Papaloukas, O. Milionis, D. Biros, C. Kyriakopoulos, K. Kostikas, H. Milionis, D.I. Fotiadis (2022) “Predicting the need for mechanical ventilation and mortality in hospitalized COVID-19 patients who received heparin”, 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- D. Katsarou, E.I. Georga, M. Christou, S. Tigas, C. Papaloukas, D.I. Fotiadis (2022) “Short Term Glucose Prediction in Patients with Type 1 Diabetes Mellitus”, 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- O.D. Papagiannopoulos, C. Papaloukas, V.C. Pezoulas, H.J.G. van de Werken, C. Poulet, Y.M. Mueller, P.D. Katsikis, D. de Seny, D.I. Fotiadis (2022) "Comparison of Proteomic Assay Methods in Autoinflammatory Disease Classification" IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
- V.C. Pezoulas, E. Mylona, C. Papaloukas, A. Liontos, D.I. Biros, O.I. Milionis, C. Kyriakopoulos, K. Kostikas, H. Milionis, D.I. Fotiadis (2022) "A hybrid approach based on dynamic trajectories to predict mortality in COVID-19 patients upon steroids administration", IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
- D.N. Katsarou, E.I. Georga, M. Christou, S. Tigas, C. Papaloukas, D.I. Fotiadis (2022) “An Exploratory Study of the Value of Vital Signs on the Short-term Prediction of Subcutaneous Glucose Concentration in Type 1 Diabetes – The GlucoseML Study” 16th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth)
2021
- A. Koloi, A.I. Sakellarios, V.C. Pezoulas, C. Papaloukas, M. Kleber, W. März, D.I. Fotiadis (2021) "Coronary Artery Stenosis Prediction using Machine Learning Algorithms", IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
2020
- K. Kourou, V. Pezoulas, E. Georga, Th. Exarchos, C. Papaloukas, M. Voulgarelis, A. Goules, A. Nezos, A.G. Tzioufas, Η.M. Moutsopoulos, C. Mavragani, D.I. Fotiadis (2020) "Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren's Syndrome Patients" IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) 1: 49-56.
2019
- K. Kourou, C. Papaloukas, D.I. Fotiadis (2019) "Modeling biological data through dynamic bayesian networks for oral squamous cell carcinoma classification" World Congress on Medical Physics and Biomedical Engineering (2018) pp. 375-9.
2015
- Kourou, K., Exarchos, T. P., Exarchos, K. P., Karamouzis, M. V. & Fotiadis, D. I. (2015) Machine learning applications in cancer prognosis and prediction. Computational and structural biotechnology journal 13, 8-17.
