Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …

Deep Learning (DL) has gained enormous popularity recently; however, it is an opaque
technique that is regarded as a black box. To ensure the validity of the model's prediction, it …

Interpreting machine learning models is facilitated by the widely employed locally
interpretable model-agnostic explanation (LIME) technique. However, when extending LIME …

Cardiac arrhythmia is a cardiac irregularity that impacts a significant number of individuals
globally. Certain arrhythmias may be benign or occur only once, while recurring arrhythmias …

The vast majority of healthcare systems are operating at or near their full capacity. Providing
an inaccurate diagnosis is a further prevalent issue. Although it is common knowledge that …

This paper focuses on explaining changes over time in globally sourced annual temporal
data with the specific objective of identifying features in black-box models that contribute to …

The accurate classification of arrhythmias is crucial for effective cardiac diagnosis and
treatment. Recently, there have been numerous studies aimed at diagnosing arrhythmias; …

This paper focuses on explaining changes over time in globally-sourced, annual temporal
data, with the specific objective of identifying pivotal factors that contribute to these temporal …

The ECG and PPG signals contribute for the state machine learning logic and enables
prompt diagnostic interpretation both in spatial and frequency domain. Analysis of …

Rapid advancements in networks and computer systems have opened a new door for
immoral acts like cybercrime, which threaten public safety, and security, as well as the global …