Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability
to explain the complex decision-making process of machine learning (ML) and deep …

Abstract Context: Artificial Intelligence (AI) in the medical domain has achieved remarkable
results on various metrics primarily due to recent advancements in computational …

The unprecedented growth of computational capabilities in recent years has allowed
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …

The Alzheimer′ s Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge is
the most comprehensive challenge to date with regard to the number of subjects, considered …

Background Due to the class imbalance issue faced when Alzheimer's disease (AD)
develops from normal cognition (NC) to mild cognitive impairment (MCI), present clinical …

Directing research on Alzheimer's disease toward only early prediction and accuracy cannot
be considered a feasible approach toward tackling a ubiquitous degenerative disease …

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and
progression detection have been intensively studied. Nevertheless, research studies often …

Individuals diagnosed with Mild Cognitive Impairment (MCI) have shown an increased risk
of developing Alzheimer's Disease (AD). As such, early identification of dementia represents …

Abstract Modern Artificial Intelligence (AI) models offer high predictive accuracy but often
lack interpretability with respect to reasons for predictions. Explanations for predictions are …

In domains such as medical and healthcare, the interpretability and explainability of
machine learning and artificial intelligence systems are crucial for building trust in their …