location_onAmphi 125
Conférence

Rethinking Artistic Creation with Gen AI through SMARTANIMA

calendar_today 2 avril 2026
schedule 15h45–16h15
Speakers
Vazilis PezoulasUniversity of Ioannina
Dimitrios FotiadisUniversity of Ioannina
Biography
Dimitrios Fotiadis
Professeur d'ingénierie biomédicale, directeur du MedLab
Dimitrios I. Fotiadis is Professor of Biomedical Engineering at the University of Ioannina and Director of the Unit of Medical Technology and Intelligent Information Systems (MedLab). His research covers multiscale modelling of human tissues, intelligent wearable/implantable devices, big medical data processing, and machine learning. He served as Editor-in-Chief of the IEEE Journal of Biomedical and Health Informatics (2017–2024) and has over 500 journal articles with an h-index of 86 and 36,000+ citations.
open_in_newAcademic profile
Abstract
Abstract coming soon
Selected bibliography
  • Tsiouris, Κ. Μ., Pezoulas, V. C., Zervakis, M., Konitsiotis, S., Koutsouris, D., Fotiadis, D. I. (2018). A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals. Computers in Biology and Medicine, 99, 24–37. https://doi.org/10.1016/j.compbiomed.2018.05.019
  • Pezoulas, V. C., Zaridis, D. I., Mylona, E., Androutsos, C., Apostolidis, K., Tachos, N. S., Fotiadis, D. I. (2024). Synthetic data generation methods in healthcare: A review on open-source tools and methods. Computational and Structural Biotechnology Journal, 23, 2892–2910. https://doi.org/10.1016/j.csbj.2024.07.005
  • Pezoulas, V. C., Κούρου, Κ., Kalatzis, F., Exarchos, T. P., Venetsanopoulou, A. I., Zampeli, E., Gandolfo, S., Skopouli, F. N., Vita, S. D., Tzioufas, A. G., Fotiadis, D. I. (2019). Medical data quality assessment: On the development of an automated framework for medical data curation. Computers in Biology and Medicine, 107, 270–283. https://doi.org/10.1016/j.compbiomed.2019.03.001
  • Goules, A. V., Argyropoulou, O. D., Pezoulas, V. C., Chatzis, L., Critselis, E., Gandolfo, S., Ferro, F., Binutti, M., Donati, V., Callegher, S. Z., Venetsanopoulou, A. I., Zampeli, E., Mavrommati, M., Voulgari, P. V., Exarchos, T. P., Mavragani, C. P., Baldini, C., Skopouli, F. N., Fotiadis, D. I., ... Tzioufas, A. G. (2020). Primary Sjögren’s Syndrome of Early and Late Onset: Distinct Clinical Phenotypes and Lymphoma Development. Frontiers in Immunology, 11, 594096–594096. https://doi.org/10.3389/fimmu.2020.594096
  • Chatzis, L., Stergiou, I. Ε., Goules, A. V., Pezoulas, V. C., Tsourouflis, G., Fotiadis, D. I., Tzioufas, A. G., Voulgarelis, M. (2021). Clinical picture, outcome and predictive factors of lymphoma in primary Sjögren’s syndrome: results from a harmonized dataset (1981–2021). Lara D. Veeken, 61(9), 3576–3585. https://doi.org/10.1093/rheumatology/keab939
  • Tzioufas, A. G., Bakasis, A., Goules, A. V., Bitzogli, K., Cinoku, I. I., Chatzis, L., Argyropoulou, O. D., Venetsanopoulou, A. I., Mavrommati, M., Stergiou, I. Ε., Pezoulas, V. C., Voulgari, P. V., Katsimpari, C., Katechis, S., Gazi, S., Katsifis, G., Sfontouris, C., Georgountzos, A., Liossis, S. C., ... Moutsopoulos, H. Μ. (2021). A prospective multicenter study assessing humoral immunogenicity and safety of the mRNA SARS-CoV-2 vaccines in Greek patients with systemic autoimmune and autoinflammatory rheumatic diseases. Journal of Autoimmunity, 125, 102743–102743. https://doi.org/10.1016/j.jaut.2021.102743
  • Κούρου, Κ., Exarchos, T. P., Exarchos, K., Karamouzis, M. V., Fotiadis, D. I. (2014). Machine learning applications in cancer prognosis and prediction. Computational and Structural Biotechnology Journal, 13, 8–17. https://doi.org/10.1016/j.csbj.2014.11.005
  • Tzallas, A. T., Tsipouras, M. G., Fotiadis, D. I. (2009). Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis. IEEE Transactions on Information Technology in Biomedicine, 13(5), 703–710. https://doi.org/10.1109/titb.2009.2017939
  • Tsiouris, Κ. Μ., Pezoulas, V. C., Zervakis, M., Konitsiotis, S., Koutsouris, D., Fotiadis, D. I. (2018). A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals. Computers in Biology and Medicine, 99, 24–37. https://doi.org/10.1016/j.compbiomed.2018.05.019
  • Tzallas, A. T., Tsipouras, M. G., Fotiadis, D. I. (2007). Automatic Seizure Detection Based on Time-Frequency Analysis and Artificial Neural Networks. Computational Intelligence and Neuroscience, 2007, 1–13. https://doi.org/10.1155/2007/80510
  • Tsiknakis, N., Theodoropoulos, D., Manikis, G. C., Ktistakis, E., Boutsora, O., Bertó, A., Scarpa, F., Scarpa, A., Fotiadis, D. I., Marias, K. (2021). Deep learning for diabetic retinopathy detection and classification based on fundus images: A review. Computers in Biology and Medicine, 135, 104599–104599. https://doi.org/10.1016/j.compbiomed.2021.104599
  • Voltairas, P., Fotiadis, D. I., Michalis, L. K. (2002). Hydrodynamics of magnetic drug targeting. Journal of Biomechanics, 35(6), 813–821. https://doi.org/10.1016/s0021-9290(02)00034-9