| Stroke risk prediction with machine learning techniques E Dritsas, M Trigka Sensors 22 (13), 4670, 2022 | 193 | 2022 |
| Lung cancer risk prediction with machine learning models E Dritsas, M Trigka Big Data and Cognitive Computing 6 (4), 139, 2022 | 94 | 2022 |
| Machine learning techniques for chronic kidney disease risk prediction E Dritsas, M Trigka Big Data and Cognitive Computing 6 (3), 98, 2022 | 77 | 2022 |
| Data-driven machine-learning methods for diabetes risk prediction E Dritsas, M Trigka Sensors 22 (14), 5304, 2022 | 73 | 2022 |
| Supervised machine learning models for liver disease risk prediction E Dritsas, M Trigka Computers 12 (1), 19, 2023 | 59 | 2023 |
| Efficient data-driven machine learning models for cardiovascular diseases risk prediction E Dritsas, M Trigka Sensors 23 (3), 1161, 2023 | 55 | 2023 |
| Long-term coronary artery disease risk prediction with machine learning models M Trigka, E Dritsas Sensors 23 (3), 1193, 2023 | 37 | 2023 |
| Efficient data-driven machine learning models for water quality prediction E Dritsas, M Trigka Computation 11 (2), 16, 2023 | 32 | 2023 |
| Machine learning methods for hypercholesterolemia long-term risk prediction E Dritsas, M Trigka Sensors 22 (14), 5365, 2022 | 27 | 2022 |
| 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 |
| Trajectory clustering and k-NN for robust privacy preserving spatiotemporal databases E Dritsas, M Trigka, P Gerolymatos, S Sioutas Algorithms 11 (12), 207, 2018 | 15 | 2018 |
| Supervised machine learning models to identify early-stage symptoms of sars-cov-2 E Dritsas, M Trigka Sensors 23 (1), 40, 2022 | 12 | 2022 |
| A multi-class classification approach for weather forecasting with machine learning techniques E Dritsas, M Trigka, P Mylonas 2022 17th International Workshop on Semantic and Social Media Adaptation
, 2022 | 11 | 2022 |
| The predictive power of a twitter users profile on cryptocurrency popularity M Trigka, A Kanavos, E Dritsas, G Vonitsanos, P Mylonas Big Data and Cognitive Computing 6 (2), 59, 2022 | 11 | 2022 |
| A survey on signal processing methods for EEG-based brain computer interface systems M Trigka, E Dritsas, C Fidas Proceedings of the 26th Pan-Hellenic Conference on Informatics, 213-218, 2022 | 9 | 2022 |
| Storage Efficient Trajectory Clustering and k-NN for Robust Privacy Preserving Spatio-Temporal Databases E Dritsas, A Kanavos, M Trigka, S Sioutas, A Tsakalidis Algorithms 12 (12), 266, 2019 | 9 | 2019 |
| Museum guidance in sign language: The signguide project D Kosmopoulos, C Constantinopoulos, M Trigka, D Papazachariou, ... Proceedings of the 15th International Conference on PErvasive Technologies
, 2022 | 8 | 2022 |
| Trajectory Clustering and k-NN for Robust Privacy Preserving k-NN Query Processing in GeoSpark E Dritsas, A Kanavos, M Trigka, G Vonitsanos, S Sioutas, A Tsakalidis Algorithms 13 (8), 182, 2020 | 8 | 2020 |
| Mental confusion prediction in e-learning contexts with eeg and machine learning M Trigka, E Dritsas, P Mylonas Novel & Intelligent Digital Systems Conferences, 195-200, 2023 | 7 | 2023 |
| Predicting the occurrence of metabolic syndrome using machine learning models M Trigka, E Dritsas Computation 11 (9), 170, 2023 | 7 | 2023 |
Elias Dritsas"ATHENA" Research Center \ Industrial Systems Institute and University of Patras, GreecePatvirtintas el. paštas ceid.upatras.gr
