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A. Karasmanoglou, M. Antonakakis and M. Zervakis, "Heatmap-based explanation of YOLOv5 object detection with layer-wise relevance propagation," in Proceedings of the 2022 IEEE International Conference on Imaging Systems and Techniques (IST 2022), Kaohsiung, Taiwan, 2022, doi: 10.1109/IST55454.2022.9827744.
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S. Tsakaneli, E. S. Bei and M. E. Zervakis, "A 21-hub-gene signature in multiple sclerosis identified using machine learning techniques," in Proceedings of the 2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI 2022), Ioannina, Greece, 2022, doi: 10.1109/BHI56158.2022.9926949.
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A. Grammatikopoulou, N. Grammalidis, M. Papadogiorgaki and M. Zervakis, “A platform for health emergency warning and wandering behaviour detection supporting people with intellectual disability,” in Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments (PETRA 2022), Corfu, Greece, pp. 694–699, July 2022, doi: 10.1145/3529190.3534773.
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N. J. Simos, K. Manolitsi, A. I. Luppi, A. Kagialis, M. Antonakakis, M. Zervakis, D. Antypa, E. Kavroulakis, T. G. Maris, A. Vakis, E. A. Stamatakis and E. Papadaki “Chronic mild Traumatic Brain Injury: aberrant static and dynamic connectomic features identified through machine learning model fusion,” Neuroinform., vol. 21, no. 2, pp. 427–442, Apr. 2023, doi: 10.1007/s12021-022-09615-1.
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T. N. Papadomanolakis, E. S. Sergaki, A. A. Polydorou, A. G. Krasoudakis, G. N. Makris-Tsalikis, A. A. Polydorou, N. M. Afentakis, S. A. Athanasiou, I. O. Vardiambasis, and M. E. Zervakis, “Tumor diagnosis against other brain diseases using T2 MRI brain images and CNN binary classifier and DWT,” Brain Sci., vol. 13, no. 2, Feb. 2023, doi: 10.3390/brainsci13020348.
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A. Vogiatzis, S. Orfanoudakis, G. Chalkiadakis, K. Moirogiorgou and M. Zervakis, “Novel meta-learning techniques for the multiclass image classification problem,” Sensors, vol. 23, no. 1, Jan. 2023, doi: 10.3390/s23010009.
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S. A. Athanasiou, E. S. Sergaki, A. A. Polydorou, A. A. Polydorou, G. S. Stavrakakis, N. M. Afentakis, I. O. Vardiambasis, and M. E. Zervakis “Revealing the boundaries of selected gastro-intestinal (GI) organs by implementing CNNs in endoscopic capsule images,” Diagnostics, vol. 13, no. 5, Feb. 2023, doi: 10.3390/diagnostics13050865.
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T. Medani, J. Garcia-Prieto, F. Tadel, M. Antonakakis, T. Erdbrügger, M. Höltershinken, W. Mead, S. Schrader, A. Joshi, C. Engwer, C. H. Wolters, J. C. Mosher, and R. M. Leahy, “Brainstorm-DUNEuro: an integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity,” NeuroImage, vol. 267, Feb. 2023, doi: 10.1016/j.neuroimage.2022.119851.
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A. Dovrou, E. Bei, S. Sfakianakis, K. Marias, N. Papanikolaou and M. Zervakis, “Synergies of radiomics and transcriptomics in lung cancer diagnosis: a pilot study,” Diagnostics, vol. 13, no. 4, Feb. 2023, doi: 10.3390/diagnostics13040738.
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E. Trivizakis, N.-M. Koutroumpa, J. Souglakos, A. Karantanas, M. Zervakis and K. Marias, “Radiotranscriptomics of non-small cell lung carcinoma for assessing high-level clinical outcomes using a machine learning-derived multi-modal signature,” BioMed. Eng. OnLine, vol. 22, no. 1, Dec. 2023, doi: 10.1186/s12938-023-01190-z.