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20202025
most citedA comprehensive interpretable machine learning framework for Mild Cognitive Impairment and Alzheimer's disease diagnosis

33 citations · 77 across the 7 of their papers we have counts for

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cs.LG2025

Comparative assessment of fairness definitions and bias mitigation strategies in machine learning-based diagnosis of Alzheimer's disease from MR images

Maria Eleftheria Vlontzou, Maria Athanasiou, Christos Davatzikos +1

The present study performs a comprehensive fairness analysis of machine learning (ML) models for the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) from…

cs.LG2025★ 3 cited

A modular framework for automated evaluation of procedural content generation in serious games with deep reinforcement learning agents

Eleftherios Kalafatis, Konstantinos Mitsis, Konstantia Zarkogianni +2

Serious Games (SGs) are nowadays shifting focus to include procedural content generation (PCG) in the development process as a means of offering personalized and enhanced player ex…

cs.LG2024★ 33 cited

A comprehensive interpretable machine learning framework for Mild Cognitive Impairment and Alzheimer's disease diagnosis

Maria Eleftheria Vlontzou, Maria Athanasiou, Kalliopi Dalakleidi +3

An interpretable machine learning (ML) framework is introduced to enhance the diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) by ensuring robustness of th…

cs.LG2022★ 23 cited

Interpretability methods of machine learning algorithms with applications in breast cancer diagnosis

Panagiota Karatza, Kalliopi V. Dalakleidi, Maria Athanasiou +1

Early detection of breast cancer is a powerful tool towards decreasing its socioeconomic burden. Although, artificial intelligence (AI) methods have shown remarkable results toward…