Maria Athanasiou
Orcid: 0000-0001-8350-3567
According to our database1,
Maria Athanasiou authored at least 19 papers
between 2007 and 2026.
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Bibliography
2026
Interpretable Graph Convolutional Networks for cardiovascular disease risk prediction in patients with Type 2 Diabetes Mellitus.
J. Biomed. Informatics, 2026
2025
A Modular Framework for Automated Evaluation of Procedural Content Generation in Serious Games With Deep Reinforcement Learning Agents.
IEEE Trans. Games, December, 2025
Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images.
CoRR, May, 2025
Gut Microbial Signatures for Early Screening of Autism Spectrum Disorder: An Interpretable Machine Learning Approach.
Proceedings of the 25th IEEE International Conference on Bioinformatics and Bioengineering, 2025
Comparative Assessment of Uncertainty-Aware Deep Learning Methods for Atherosclerosis Risk Stratification from Carotid Ultrasound Imaging.
Proceedings of the 25th IEEE International Conference on Bioinformatics and Bioengineering, 2025
Fairness-Aware Deep Learning Model for Covid19 Detection from Cough Audio Recordings.
Proceedings of the 25th IEEE International Conference on Bioinformatics and Bioengineering, 2025
Development of an Interpretable and Uncertainty-Aware Deep Learning Model for Gastric Cancer Histopathological Image Classification.
Proceedings of the 25th IEEE International Conference on Bioinformatics and Bioengineering, 2025
2024
A comprehensive interpretable machine learning framework for Mild Cognitive Impairment and Alzheimer's disease diagnosis.
CoRR, 2024
Sustaining model performance for covid-19 detection from dynamic audio data: Development and evaluation of a comprehensive drift-adaptive framework.
CoRR, 2024
Development of personalized interpretable multilevel prediction models for the risk assessment of hypoglycemia in Type 1 Diabetes.
Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024
Uncertainty-Informed Active Learning Using Monte Carlo Dropout for Risk Stratification in Carotid Ultrasound Imaging.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2024
2022
Artificial Intelligence Based Procedural Content Generation in Serious Games for Health: The Case of Childhood Obesity.
Proceedings of the Wireless Mobile Communication and Healthcare, 2022
2021
Interpretability methods of machine learning algorithms with applications in breast cancer diagnosis.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Stratification of carotid atheromatous plaque using interpretable deep learning methods on B-mode ultrasound images.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
An LSTM-based Approach Towards Automated Meal Detection from Continuous Glucose Monitoring in Type 1 Diabetes Mellitus.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021
2020
An explainable XGBoost-based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020
2019
An Ontology-Based Serious Game Design for the Development of Nutrition and Food Literacy Skills.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
Comparison of Machine Learning Approaches Toward Assessing the Risk of Developing Cardiovascular Disease as a Long-Term Diabetes Complication.
IEEE J. Biomed. Health Informatics, 2018
2007
A Bayesian Network Model for the Diagnosis of the Caring Procedure for Wheelchair Users with Spinal Injury.
Proceedings of the 20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), 2007