K. Zarkogianni
- smarty4covid project (Greek funded), Greece: Intelligent Multimodal Framework for COVID-19 Risk Assessment and Monitoring based on Explainable Deep Learning.
- ENDORSE project (Greek funded), Greece: A comprehensive approach to empower self-management of health in children and adolescents with Type 1 Diabetes Mellitus and/or Obesity based on gamification mechanisms and biofeedback.
- MOSAIC project (European funded – FP7): Models and simulation techniques for discovering diabetes influence factors.
- SMARTDIAB project (Greek Funded), Greece: An Insulin Infusion Intelligent System.
- Member of the B3 Action Plan of the European Innovation Partnership on Active and Healthy Ageing (EIP AHA)
Peer-reviewed journal publications
- K. Zarkogianni, E. Dervakos, G. Filandrianos, T. Ganitidis, V. Gkatzou, A. Sakagianni, R. Raghavendra, C.L. Max Nikias, G. Stamou, and K. S. Nikita, “The smarty4covid dataset and knowledge base: a framework enabling interpretable analysis of audio signals,” accepted for publication at the Springer - Nature Scientific Data
- P. Pervanidou, E. Chatzidaki, M.C. Nicolaides, A. Voutetakis, N. Polychronaki, V. Chioti, R. A. Kitani, E. Kyrkopoulou, K. Zarkogianni, E. Kalafatis, K. Mitsis, K. Perakis, K. S. Nikita, and C. Kanaka-Gantenbein, “The Impact of the ENDORSE Digital Weight Management Program on the Metabolic Profile of Children and Adolescents with Overweight and Obesity and on Food Parenting Practices,” Nutrients, vol. 15, no. 7, p. 1777, 2023.
- K. Zarkogianni, E. Chatzidaki, N. Polychronaki, E. Kalafatis, N. C. Nicolaides, A. Voutetakis, V. Chioti, R. A. Kitani, K. Mitsis, K. Perakis, M. Athanasiou, D. Antonopoulou, P. Pervanidou, C. Kanaka-Gantenbein and K. S. Nikita, “The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity,” Nutrients, vol. 15, no. 6, p. 1451, 2023.
- M. Athanasiou, G. Fragkozidis, K. Zarkogianni, K. S. Nikita, “Prediction of the spread of influenza-like-illness using Long Short-Term Memory architectures based on surveillance, weather, and Twitter data”, Journal of Medical Internet Research, vol. 25, e42519, 2023.
- K. Mitsis, K. Zarkogianni, E. Kalafatis, K. Dalakleidi, A. Jaafar, G. Mourkousis, K. S. Nikita, “A Multimodal Approach for Real Time Recognition of Engagement towards Adaptive Serious Games for Health”, Sensors, vol. 22, Issue 7, 2022
- G. Fico, L. Hernanzez, J. Cancela, A. Dagliati, L. Sacchi, A. Martinez-Millana, J. Posada, L. Manero, J. Verdú, A. Facchinetti, M. Ottaviano, K. Zarkogianni, K. Nikita, L. Groop, R. Gabriel-Sanchez, L. Chiovato, V. Traver, J. Francisco Merino-Torres, C. Cobelli, R. Bellazzi, M. T. Arredondo, “What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project”, BMC medical informatics and decision making, vol. 19, pp. 1-16, 2019
- K. Zarkogianni, M. Athanasiou, A. C. Thanopoulou, and K. S. Nikita, “Comparison of machine learning approaches towards assessing the risk of developing Cardiovascular disease as a long-term diabetes complication”, IEEE Journal of Biomedical and Health Informatics, vol. 22, pp.1637-1647, 2018.
- K. Dalakleidi, K. Zarkogianni, A. Thanopoulou, and K. Nikita, “Comparative Assessment of Statistical and Machine Learning Techniques Towards Estimating the Risk of Developing Type 2 Diabetes and Cardiovascular Complications”, Expert Systems, e12214, 2017.
- J. Verdú, F. Sambo, B. Di Camillo, C. Cobelli, A. Facchinetti, G. Fico, R. Bellazzi, L. Sacchi, A. Dagliati, D. Segnani, V. Tibollo, M. Ottaviano, R. Gabriel, L. Groop, J. Postma, A. Martinez, L. Hakaste, T. Tuomi, and K. Zarkogianni, “Predictive, preventive and personalized medicine in diabetes onset and complication (MOSAIC project)”, The EPMA Journal, vol. 7, Suppl. 1, pp 42-43, 2016.
- L. Spanou, K. Dalakleidi, K. Zarkogianni, P. Anastasia, K. Nikita, V. Vasiliki, M. Alevizaki, E. Anastasiou, “Ketonemia and ketonuria in gestational diabetes mellitus”, Hormones, vol. 14, pp. 644-650, 2015.
- K. Zarkogianni, E. Litsa, K. Mitsis, P. Wu, C.D. Kaddi, C. Cheng, M. D. Wang, K. S. Nikita, "A Review of Emerging Technologies for the Management of Diabetes Mellitus", IEEE Transactions on Biomedical Engineering, vol. 62, no. 12, pp.2735-2749, 2015.
- K. Zarkogianni, K. Mitsis, E. Litsa, MT Arredondo, G. Fico, A. Fioravanti, K. S. Nikita, “Comparative assessment of glucose prediction models for Patients with Type 1 Diabetes Mellitus applying sensors for glucose and physical activity monitoring”, Medical & Biological Engineering & Computing, vol. 53, no. 12, pp. 1333-1343, 2015.
- K. Zarkogianni, A. Vazeou, S.G. Mougiakakou, A. Prountzou, K.S. Nikita, "An insulin infusion advisory system based on autotuning nonlinear model-predictive control", IEEE Transactions on Biomedical Engineering, vol. 58, no. 9, pp. 2467-77, 2011.
- S.G. Mougiakakou, C. Bartsocas, E. Bozas, N. Chaniotakis, D. Iliopoulou, I. Kouris, S. Pavlopoulos, A. Prountzou, M. Skevofylakas, A. Tsoukalis, K. Varotsis, A. Vazeou, K. Zarkogianni and K. S. Nikita, "SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and Follow-up of Type 1 Diabetes Patients", IEEE Transactions on Information Technology in Biomedicine, Special Issue: New and Emerging Trends in Bioinformatics and Bioengineering, vo. 14, no. 3, pp. 622 – 633, 2010.
- S. Mougiakakou, A. Prountzou, K. Zarkogianni, C. Bartsocas, K. Nikita, A. Gerasimidi-Vazeou, "Prediction of glucose profile in children with type 1 diabetes mellitus using continuous glucose monitors and insulin pumps", Hormone Research, vol. 70, Suppl. 1, pp. 22-23, 2008.
K. Zarkogianni
Associate Professor
Dept. of Advanced Computing Sciences
Faculty of Science and Engineering