| A review of emerging technologies for the management of diabetes mellitus K Zarkogianni, E Litsa, K Mitsis, PY Wu, CD Kaddi, CW Cheng, MD Wang, ... IEEE Transactions on Biomedical Engineering 62 (12), 2735-2749, 2015 | 154 | 2015 |
| SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients SG Mougiakakou, CS Bartsocas, E Bozas, N Chaniotakis, D Iliopoulou, ... IEEE Transactions on Information Technology in Biomedicine 14 (3), 622-633, 2010 | 129 | 2010 |
| Comparative assessment of glucose prediction models for patients with type 1 diabetes mellitus applying sensors for glucose and physical activity monitoring K Zarkogianni, K Mitsis, E Litsa, MT Arredondo, G Ficο, A Fioravanti, ... Medical & biological engineering & computing 53, 1333-1343, 2015 | 128 | 2015 |
| An insulin infusion advisory system based on autotuning nonlinear model-predictive control K Zarkogianni, A Vazeou, SG Mougiakakou, A Prountzou, KS Nikita IEEE Transactions on Biomedical Engineering 58 (9), 2467-2477, 2011 | 115 | 2011 |
| Comparison of machine learning approaches toward assessing the risk of developing cardiovascular disease as a long-term diabetes complication K Zarkogianni, M Athanasiou, AC Thanopoulou, KS Nikita IEEE journal of biomedical and health informatics 22 (5), 1637-1647, 2017 | 88 | 2017 |
| An explainable XGBoost–based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus M Athanasiou, K Sfrintzeri, K Zarkogianni, AC Thanopoulou, KS Nikita 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering …, 2020 | 80 | 2020 |
| A hybrid Decision Support System for the risk assessment of retinopathy development as a long term complication of Type 1 Diabetes Mellitus M Skevofilakas, K Zarkogianni, BG Karamanos, KS Nikita 2010 Annual International Conference of the IEEE Engineering in Medicine and …, 2010 | 68 | 2010 |
| Artificial intelligence and machine learning for improving glycemic control in diabetes: Best practices, pitfalls, and opportunities PG Jacobs, P Herrero, A Facchinetti, J Vehi, B Kovatchev, MD Breton, ... IEEE reviews in biomedical engineering 17, 19-41, 2023 | 49 | 2023 |
| Comparative assessment of statistical and machine learning techniques towards estimating the risk of developing type 2 diabetes and cardiovascular complications K Dalakleidi, K Zarkogianni, A Thanopoulou, K Nikita Expert Systems 34 (6), e12214, 2017 | 42 | 2017 |
| Personalized glucose-insulin metabolism model based on self-organizing maps for patients with Type 1 Diabetes Mellitus K Zarkogianni, E Litsa, A Vazeou, KS Nikita 13th IEEE International Conference on BioInformatics and BioEngineering, 1-4, 2013 | 38 | 2013 |
| An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods K Zarkogianni, SG Mougiakakou, A Prountzou, A Vazeou, CS Bartsocas, ... 2007 29th Annual International Conference of the IEEE Engineering in …, 2007 | 38 | 2007 |
| Ketonemia and ketonuria in gestational diabetes mellitus L Spanou, K Dalakleidi, K Zarkogianni, A Papadimitriou, K Nikita, ... Hormones 14 (4), 644-650, 2015 | 34 | 2015 |
| A hybrid genetic algorithm for the selection of the critical features for risk prediction of cardiovascular complications in Type 2 Diabetes patients KV Dalakleidi, K Zarkogianni, VG Karamanos, AC Thanopoulou, KS Nikita 13th IEEE International Conference on BioInformatics and BioEngineering, 1-4, 2013 | 34 | 2013 |
| Neuro-fuzzy based glucose prediction model for patients with Type 1 diabetes mellitus K Zarkogianni, K Mitsis, MT Arredondo, G Fico, A Fioravanti, KS Nikita IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI …, 2014 | 32 | 2014 |
| An ontology-based serious game design for the development of nutrition and food literacy skills K Mitsis, K Zarkogianni, N Bountouni, M Athanasiou, KS Nikita 2019 41st annual international conference of the IEEE Engineering in …, 2019 | 30 | 2019 |
| A data gathering framework to collect type 2 diabetes patients data A Dagliati, L Sacchi, M Bucalo, D Segagni, K Zarkogianni, AM Millana, ... IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI …, 2014 | 24 | 2014 |
| Long short-term memory–based prediction of the spread of influenza-like illness leveraging surveillance, weather, and twitter data: Model development and validation M Athanasiou, G Fragkozidis, K Zarkogianni, KS Nikita Journal of Medical Internet Research 25, e42519, 2023 | 22 | 2023 |
| Personal health systems for diabetes management, early diagnosis and prevention K Zarkogianni, KS Nikita Consumer-Driven Technologies in Healthcare: Breakthroughs in Research and …, 2019 | 22 | 2019 |
| 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 G Fico, L Hernanzez, J Cancela, A Dagliati, L Sacchi, A Martinez-Millana, ... BMC medical informatics and decision making 19, 1-16, 2019 | 19 | 2019 |
| Prediction of glucose profile in children with type 1 diabetes mellitus using continuous glucose monitors and insulin pumps S Mougiakakou, A Prountzou, K Zarkogianni, C Bartsocas, K Nikita, ... | 18 | 2008 |
Konstantina NikitaProfessor, School of Electrical and Computer Engineering, National Technical University of AthensGeverifieerd e-mailadres voor ece.ntua.gr