This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

Alzheimer disease (AD) is among the most chronic neurodegenerative diseases that
threaten global public health. The prevalence of Alzheimer disease and consequently the …

The current study investigates the robustness of deep learning models for accurate medical
diagnosis systems with a specific focus on their ability to maintain performance in the …

In recent years, Artificial Intelligence (AI) methods, specifically Machine Learning (ML)
models, have been providing outstanding results in different areas of knowledge, with the …

Introduction Primary Progressive Aphasia (PPA) is a neurodegenerative disease
characterized by linguistic impairment. The two main clinical subtypes are semantic (svPPA) …

Respiratory system cancer, encompassing lung, trachea and bronchus cancer, constitute a
substantial and evolving public health challenge. Since pollution plays a prominent cause in …

Explainable AI (XAI) in medical histopathology is essential for enhancing the interpretability
and clinical trustworthiness of deep learning models in cancer diagnosis. However, the …

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 …

The complex nature of disease mechanisms and the variability of patient symptoms present
significant obstacles in developing effective diagnostic tools. Although machine learning has …

Functional connectivity derived from functional Magnetic Resonance Imaging (fMRI) data
has been increasingly used to study brain activity. In this study, we model brain dynamic …