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Research publications

Find below selected recent publications of our team demonstrating the application of AI in an variety of domains including industrial sectors, healthcare, energy and security


  • Ntakolia, C., Moustakidis, S., & Siouras, A. (2023). Autonomous path planning with obstacle avoidance for Smart Assistive Systems. Expert Systems with Applications, 213, 119049. doi:10.1016/j.eswa.2022.119049

  • Kokkotis, C., Chalatsis, G., Moustakidis, S., Siouras, A., Mitrousias, V., Tsaopoulos, D., ... & Tsatalas, T. (2022). Identifying Gait-Related Functional Outcomes in Post-Knee Surgery Patients Using Machine Learning: A Systematic Review. International Journal of Environmental Research and Public Health, 20(1), 448.

  • Kokkotis, C., Moustakidis, S., Giarmatzis, G., Giannakou, E., Makri, E., Sakellari, P., ... & Aggelousis, N. (2022). Machine Learning Techniques for the Prediction of Functional Outcomes in the Rehabilitation of Post-Stroke Patients: A Scoping Review. BioMed, 3(1), 1-20.

  • Chadoulos, C. G., Tsaopoulos, D. E., Moustakidis, S., Tsakiridis, N. L., & Theocharis, J. B. (2022). A novel multi-atlas segmentation approach under the semi-supervised learning framework: Application to knee cartilage segmentation. Computer Methods and Programs in Biomedicine, 227, 107208.

  • Kopsidas, I., Karagiannidou, S., Kostaki, E. G., Kousi, D., Douka, E., Sfikakis, P. P., ... & Paraskevis, D. (2022). Global Distribution, Dispersal Patterns, and Trend of Several Omicron Subvariants of SARS-CoV-2 across the Globe. Tropical Medicine and Infectious Disease, 7(11), 373.

  • Siouras, A., Stergiou, K., Karlsson, P., & Moustakidis, S. (2022). Hybrid object detection methodology combining altitude-dependent local deep learning models for search and rescue operations. Journal of Control and Decision, 1-11. doi:10.1080/23307706.2022.2141358

  • Kampaktsis, P. N., Siouras, A., Doulamis, I. P., Moustakidis, S., Emfiezoglou, M., Van den Eynde, J., ... & Briasoulis, A. (2022). Machine learning‐based prediction of mortality after heart transplantation in adults with congenital heart disease: A UNOS database analysis. Clinical Transplantation, e14845.

  • Chadoulos, C. G., Tsaopoulos, D. E., Moustakidis, S., Tsakiridis, N. L., & Theocharis, J. B. (2022). A novel multi-atlas segmentation approach under the semi-supervised learning framework: Application to knee cartilage segmentation. Computer Methods and Programs in Biomedicine, 107208.

  • Kokkotis, C., Giarmatzis, G., Giannakou, E., Moustakidis, S., Tsatalas, T., Tsiptsios, D., ... & Aggelousis, N. (2022). An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data. Diagnostics, 12(10), 2392.

  • Papandrianos, N. I., Feleki, A., Moustakidis, S., Papageorgiou, E. I., Apostolopoulos, I. D., & Apostolopoulos, D. J. (2022). An Explainable Classification Method of SPECT Myocardial Perfusion Images in Nuclear Cardiology Using Deep Learning and Grad-CAM. Applied Sciences, 12(15), 7592.

  • Kokkotis, C., Moustakidis, S., Tsatalas, T., Ntakolia, C., Chalatsis, G., Konstadakos, S., ... & Tsaopoulos, D. (2022). Leveraging explainable machine learning to identify gait biomechanical parameters associated with anterior cruciate ligament injury. Scientific Reports, 12(1), 1-12.

  • Kampaltsis, P., Emfiezoglou, M., Siouras, A., Eynde, J., Moustakidis, S., Doulamis, I. P., ... & Briasoulis, A. (2022). Prediction of 1-Year Mortality After Heart Transplantation in Adults with Congenital Heart Disease with Machine Learning Models. The Journal of Heart and Lung Transplantation, 41(4), S436.

  • Anagnostis, A., Moustakidis, S., Papageorgiou, E., & Bochtis, D. (2022). A Hybrid Bimodal LSTM Architecture for Cascading Thermal Energy Storage Modelling. Energies, 15(6), 1959.

  • Moustakidis, S., Kokkotis, C., Tsaopoulos, D., Sfikakis, P., Tsiodras, S., Sypsa, V., ... & Paraskevis, D. (2022). Identifying Country-Level Risk Factors for the Spread of COVID-19 in Europe Using Machine Learning. Viruses, 14(3), 625.

  • Siouras, A.; Moustakidis, S.; Giannakidis, A.; Chalatsis, G.; Liampas, I.; Vlychou, M.; Hantes, M.; Tasoulis, S.; Tsaopoulos, D. Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review. Diagnostics 2022, 12, 537.

  • Moustakidis, S.; Siouras, A.; Vassis, K.; Misiris, I.; Papageorgiou, E.; Tsaopoulos, D. Prediction of Injuries in CrossFit Training: A Machine Learning Perspective. Algorithms 2022, 15, 77. https://

  • Kokkotis, C., Ntakolia, C., Moustakidis, S. et al. Explainable machine learning for knee osteoarthritis diagnosis based on a novel fuzzy feature selection methodology. Phys Eng Sci Med (2022).


  • S. Moustakidis, P. Kampaktsis, A. Tzani, I. Doulamis, A. Tzoumas, A. Drosou, G. Filippatos, A. Briasoulis, Machine Learning Based Prediction of 1-year Survival after Isolated Heart Transplant, The Journal of Heart and Lung Transplantation, 40, 4, Supplement, 2021,

  • Ntakolia, C.; Kokkotis, C.; Moustakidis, S.; Tsaopoulos, D. Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients. Diagnostics 2021, 11, 285.

  • Kokkotis, C.; Moustakidis, S.; Baltzopoulos, V.; Giakas, G.; Tsaopoulos, D. Identifying Robust Risk Factors for Knee Osteoarthritis Progression: An Evolutionary Machine Learning Approach. Healthcare 2021, 9, 260.

  • Ntakolia, C., Anagnostis, A., Moustakidis, S. et al. Machine learning applied on the district heating and cooling sector: a review. Energy Systems 2021.

  • Ntakolia, C., Kokkotis, C., Moustakidis, S., & Tsaopoulos, D. (2021). Identification of most important features based on a fuzzy ensemble technique: Evaluation on joint space narrowing progression in knee osteoarthritis patients. International journal of medical informatics, 156, 104614.

  • Dikopoulou, Z., Moustakidis, S., & Karlsson, P. (2021). GLIME: A new graphical methodology for interpretable model-agnostic explanations. arXiv preprint arXiv:2107.09927.

  • Kampaktsis, P. N., Tzani, A., Doulamis, I. P., Moustakidis, S., Drosou, A., Diakos, N., ... & Briasoulis, A. (2021). State‐of‐the‐art machine learning algorithms for the prediction of outcomes after contemporary heart transplantation: Results from the UNOS database. Clinical Transplantation, 35(8), e14388.

  • Ntakolia, C., Kokkotis, C., Karlsson, P., & Moustakidis, S. (2021). An Explainable Machine Learning Model for Material Backorder Prediction in Inventory Management. Sensors, 21(23), 7926.

  • Doulamis, I. P., Tzani, A., Moustakidis, S., Kampaktsis, P. N., & Briasoulis, A. (2021). Effect of Hepatitis C donor status on heart transplantation outcomes in the United States. Clinical Transplantation, 35(4), e14220.


  • Moustakidis, S., Papandrianos, N.I., Christodolou, E. et al. Dense neural networks in knee osteoarthritis classification: a study on accuracy and fairness. Neural Computing & Applications (2020).

  • K. Liakos, G. Georgakilas, S. Moustakidis, N. Sklavos & F. Plessas, Conventional and machine learning approaches as countermeasures against hardware trojan attacks. Microprocessors And Microsystems 2020, 79, 103295. doi: 10.1016/j.micpro.2020.103295

  • C. Kokkotis, S. Moustakidis, E. Papageorgiou, G. Giakas, & D. Tsaopoulos, Machine learning in knee osteoarthritis: A review. Osteoarthritis And Cartilage Open 2020, 2(3), 100069. doi: 10.1016/j.ocarto.2020.100069

  • C. Kokkotis, S. Moustakidis, G. Giakas, D. Tsaopoulos, Identification of Risk Factors and Machine Learning-Based Prediction Models for Knee Osteoarthritis Patients. Applied Sciences 2020, 10(19), 6797

  • S. Moustakidis, P. Karlsson, A novel feature extraction methodology using Siamese convolutional neural networks for intrusion detection. Cybersecurity 3(16), 2020.

  • Ntakolia, C., Diamantis, D. E., Papandrianos, N., Moustakidis, S., & Papageorgiou, E. I. (2020, December). A lightweight convolutional neural network architecture applied for bone metastasis classification in nuclear medicine: A case study on prostate cancer patients. In Healthcare (Vol. 8, No. 4, p. 493). Multidisciplinary Digital Publishing Institute.


  • S. Moustakidis, E. Christodoulou, E. Papageorgiou, C. Kokkotis, N. Papandrianos and D. Tsaopoulos, Application of machine intelligence for osteoarthritis classification: a classical implementation and a quantum perspective, Quantum Machine Intelligence, 2019. Available: 10.1007/s42484-019-00008-3 

  • S. Moustakidis, M. Omar, J. Aguirre, P. Mohajerani, and V. Ntziachristos, V., Fully automated identification of skin morphology in raster‐scan optoacoustic mesoscopy using artificial intelligence. Medical Physics, 46(9), 4046-4056, 2019. doi: 10.1002/mp.13725 

  • S. Moustakidis, I. Meintanis, G. Halikias, and N. Karcanias, An Innovative Control Framework for District Heating Systems: Conceptualisation and Preliminary Results, Resources, vol. 8, no. 1, p. 27, 2019. Available: 10.3390/resources8010027 

till 2018

  • S. Moustakidis et al., Excitation-invariant pre-processing of thermographic data, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, vol. 232, no. 4, pp. 435-446, 2018. Available: 10.1177/1748006x18770888

  • S. Moustakidis et al., Non-destructive inspection of aircraft composite materials using triple IR imaging. IFAC-PapersOnLine 2016, 49, 291-296.

  • S. Moustakidis et al., An Intelligent Methodology for Railways Monitoring Using Ultrasonic Guided Waves, Journal of Nondestructive Evaluation, vol. 33, no. 4, pp. 694–710, Oct. 2014. 

  • S. Moustakidis, G. Mallinis, N. Koutsias, J. B. Theocharis and V. Petridis, SVM-based fuzzy decision trees for classification of high spatial resolution remote sensing images, IEEE Transactions on Geoscience and Remote Sensing, 50 (1) , art. no. 5976442 , pp. 149-169, 2012. 

  • S. Moustakidis, J. B. Theocharis, and G. Giakas, A fuzzy decision tree-based SVM classifier for assessing osteoarthritis severity using ground reaction force measurements, Medical Engineering and Physics 32(10): 1145-1160, 2010. 

  • S. Moustakidis and J. B. Theocharis, SVM-FuzCoC: A novel SVM-based feature selection method using a fuzzy complementary criterion, Pattern Recognition, vol. 43, pp. 3712-3729, 2010

  • S. Moustakidis, J. B. Theocharis, and G. Giakas, Subject Recognition Based on Ground Reaction Force Measurements of Gait Signals, IEEE Transactions on Systems, Man, and Cybernetics—Part B, vol.38, no.6, pp.1476-1485, Dec. 2008


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