| Stroke risk prediction with machine learning techniques E Dritsas, M Trigka Sensors 22 (13), 4670, 2022 | 174 | 2022 |
| Machine learning tools for long-term type 2 diabetes risk prediction N Fazakis, O Kocsis, E Dritsas, S Alexiou, N Fakotakis, K Moustakas ieee Access 9, 103737-103757, 2021 | 108 | 2021 |
| Lung cancer risk prediction with machine learning models E Dritsas, M Trigka Big Data and Cognitive Computing 6 (4), 139, 2022 | 87 | 2022 |
| Machine learning techniques for chronic kidney disease risk prediction E Dritsas, M Trigka Big Data and Cognitive Computing 6 (3), 98, 2022 | 70 | 2022 |
| Data-driven machine-learning methods for diabetes risk prediction E Dritsas, M Trigka Sensors 22 (14), 5304, 2022 | 65 | 2022 |
| Supervised machine learning models for liver disease risk prediction E Dritsas, M Trigka Computers 12 (1), 19, 2023 | 52 | 2023 |
| Efficient data-driven machine learning models for cardiovascular diseases risk prediction E Dritsas, M Trigka Sensors 23 (3), 1161, 2023 | 50 | 2023 |
| Cardiovascular Disease Risk Prediction with Supervised Machine Learning Techniques E Dritsas, S Alexiou, K Moustakas 8th International Conference on Information and Communication Technologies …, 2022 | 46 | 2022 |
| Long-term coronary artery disease risk prediction with machine learning models M Trigka, E Dritsas Sensors 23 (3), 1193, 2023 | 35 | 2023 |
| An approach for Personalized Continuous Glucose Prediction with Regression Trees S Alexiou, E Dritsas, O Kocsis, K Moustakas, N Fakotakis 6th South-East Europe Design Automation, Computer Engineering, Computer …, 2021 | 31 | 2021 |
| Efficient data-driven machine learning models for water quality prediction E Dritsas, M Trigka Computation 11 (2), 16, 2023 | 27 | 2023 |
| Machine learning methods for hypercholesterolemia long-term risk prediction E Dritsas, M Trigka Sensors 22 (14), 5365, 2022 | 27 | 2022 |
| Long-term hypertension risk prediction with ml techniques in elsa database E Dritsas, N Fazakis, O Kocsis, N Fakotakis, K Moustakas Learning and Intelligent Optimization: 15th International Conference, LION …, 2021 | 26 | 2021 |
| Long-term Cholesterol Risk Prediction using Machine Learning Techniques in ELSA Database N Fazakis, E Dritsas, O Kocsis, N Fakotakis, K Moustakas 13th International Joint Conference on Computational Intelligence 1, 445-450, 2021 | 26 | 2021 |
| Sleep quality monitoring with human assisted corrections I Konstantoulas, O Kocsis, E Dritsas, N Fakotakis, K Moustakas 13th International Joint Conference on Computational Intelligence 1, 435-444, 2021 | 23 | 2021 |
| Short-term Glucose Prediction based on Oral Glucose Tolerance Test Values E Dritsas, S Alexiou, I Konstantoulas, K Moustakas 15th International Joint Conference on Biomedical Engineering Systems and …, 2022 | 21 | 2022 |
| COPD severity prediction in elderly with ML techniques E Dritsas, S Alexiou, K Moustakas Proceedings of the 15th International Conference on PErvasive Technologies …, 2022 | 20 | 2022 |
| An apache spark implementation for graph-based hashtag sentiment classification on twitter E Dritsas, IE Livieris, K Giotopoulos, L Theodorakopoulos Proceedings of the 22nd Pan-Hellenic Conference on Informatics, 255-260, 2018 | 19 | 2018 |
| A regularization-based big data framework for winter precipitation forecasting on streaming data A Kanavos, M Trigka, E Dritsas, G Vonitsanos, P Mylonas Electronics 10 (16), 1872, 2021 | 16 | 2021 |
| Optimal Team Pairing of Elder Office Employees with Machine Learning on Synthetic Data E Dritsas, N Fazakis, O Kocsis, K Moustakas, N Fakotakis 12th International Conference on Information, Intelligence, Systems …, 2021 | 14 | 2021 |
Maria TrigkaUniversity Of PatrasVerified email at ceid.upatras.gr
