Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and
assessment of clinical signs, including the characterization of a variety of motor symptoms …

Neurodegenerative diseases have shown an increasing incidence in the older population in
recent years. A significant amount of research has been conducted to characterize these …

Clinical decisions are more promising and evidence-based, hence, big data analytics to
assist clinical decision-making has been expressed for a variety of clinical fields. Due to the …

The differential diagnosis of parkinsonian syndromes is considered one of the most
challenging in neurology and error rates in the clinical diagnosis can be high even at …

Background Supervised machine learning has been proposed as a revolutionary approach
for identifying sensitive medical image biomarkers (or combination of them) allowing for …

Parkinson's disease (PD) is a common, progressive, and currently incurable
neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in …

Parkinson's disease (PD) is a devastating neurological disease that cannot be identified with
traditional plasma experiments, necessitating the development of a faster, less expensive …

In this paper, we provide an extensive overview of machine learning techniques applied to
structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We …

Advances in molecular and structural and functional neuroimaging are rapidly expanding
the complexity of neurobiological understanding of Parkinson's disease (PD). This review …

Searching for effective biomarkers is one of the most challenging tasks in the research field
of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non …