Publications

A Federated Explainable AI Model for Breast Cancer Classification

Eleni Briola, Christos Chrysanthos Nikolaidis, Vasileios Perifanis, Nikolaos Pavlidis, Pavlos Efraimidis

European Interdisciplinary Cybersecurity Conference · pp. 194-201 · 2024

Breast cancer diagnosis is a crucial domain where Explainable Artificial Intelligence (XAI) integration holds immense importance. Understanding AI model decisions not only enhances trust but also aids in treatment strategies. However, the need for…

Advancing elderly social care dropout prediction with federated learning: client selection and imbalanced data management

Christos Chrysanthos Nikolaidis, Pavlos S. Efraimidis

Cluster Computing · Vol. 28 · No. 2 · 2024

Accurate prediction of user dropout is crucial for enhancing the effectiveness of social care applications developed for the elderly. Given the sensitive nature of healthcare data, this study introduces a Federated Learning (FL) approach…

Carbon-Aware Machine Learning: A Case Study on Cellular Traffic Forecasting with Spiking Neural Networks

Theodoros Tsiolakis, Nikolaos Pavlidis, Vasileios Perifanis, Pavlos S. Efraimidis

IFIP Advances in Information and Communication Technology · pp. 178-191 · 2024

Privacy-Enhanced Television Audience Measurements

George Drosatos, Aimilia Tasidou, Pavlos S. Efraimidis

ACM Transactions on Internet Technology · Vol. 17 · No. 1 · pp. 1-29 · 2017

Internet-enabled television systems (SmartTVs) are a development that introduces these devices into the interconnected environment of the Internet of Things. We propose a privacy-preserving application for computing Television Audience Measurement (TAM) ratings. SmartTVs communicate…