Marked changes occur in the brain during people's lives, and individual rates of aging have
revealed pronounced differences, giving rise to subject-specific brainprints that are the …

The prevalence of dementia is currently increasing worldwide. This syndrome produces a
deterioration in cognitive function that cannot be reverted. However, an early diagnosis can …

Multiple sclerosis (MS) remains a challenging neurological disorder for the clinician in terms
of diagnosis and management. The growing integration of AI-based algorithms in healthcare …

Driven by the deep learning (DL) revolution, artificial intelligence (AI) has become a
fundamental tool for many biomedical tasks, including analyzing and classifying diagnostic …

The application of convolutional neural networks (CNNs) to MRI data has emerged as a
promising approach to achieving unprecedented levels of accuracy when predicting the …

Brain microstructural changes already occur in the earliest phases of Alzheimer's disease
(AD) as evidenced in diffusion magnetic resonance imaging (dMRI) literature. This study …

Artificial intelligence has become pervasive across disciplines and fields, and biomedical
image and signal processing is no exception. The growing and widespread interest on the …

Introduction Multiple sclerosis (MS) is a complex neurodegenerative disorder that affects the
brain and spinal cord. In this study, we applied a deep learning-based approach using the …

Background and aims Functional motor disorders (FMD) present a prevalent, yet
misunderstood spectrum of neurological conditions characterized by abnormal movements …

Background Deep learning (DL) is an artificial intelligence technology that has aroused
much excitement for predictive medicine due to its ability to process raw data modalities …