Type 1 Diabetes (T1D) is an autoimmune disease that affects millions of people worldwide.
A critical issue in T1D patients is the managing of Postprandial Glucose Response (PGR) …

Within the past few years, the accuracy of deep learning and machine learning models has
been improving significantly while less attention has been paid to their responsibility …

An interesting case of the well-known Dataset Shift Problem is the classification of
Electroencephalogram (EEG) signals in the context of Brain-Computer Interface (BCI). The …

Within the past few years, the accuracy of deep learning and machine learning models has
been improving significantly while less attention has been paid to their responsibility …

Type 1 diabetes mellitus (T1DM) is characterized by insulin deficiency and blood sugar
control issues. The state-of-the-art solution is the artificial pancreas (AP), which integrates …

The monitoring and management of Postprandial Glucose Response (PGR), by
administering an insulin bolus before meals, is a crucial issue in Type 1 Diabetes (T1D) …

Abstract Explainable Artificial Intelligence (XAI) aims to provide insights into the decision-
making process of AI models, allowing users to understand their results beyond their …

Recent advances in deep learning (DL) have brought tremendous gains in signal
modulation classification. However, DL-based classifiers lack transparency and …

Abstract Explainable Artificial Intelligence (XAI) is a field usually dedicated to offering
insights into the decisionmaking mechanisms of AI models. Its purpose is to enable users to …

The rapidly growing research area of eXplainable Artificial Intelligence (XAI) focuses on
making Machine Learning systems' decisions more transparent and humanly …