Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …

Background: Artificial intelligence (AI) provides opportunities to identify the health risks of
patients and thus influence patient safety outcomes. Objective: The purpose of this …

Background Early and accurate diagnosis of Alzheimer's disease (AD) is essential for
disease management and therapeutic choices that can delay disease progression. Machine …

Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …

Support vector machines (SVMs) are well-known machine learning algorithms for
classification and regression applications. In the healthcare domain, they have been used …

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Background The improvement of health indicators and life expectancy, especially in
developed countries, has led to population growth and increased age-related diseases …

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 …

Purpose The required training sample size for a particular machine learning (ML) model
applied to medical imaging data is often unknown. The purpose of this study was to provide …

There is an increasing role for biological markers (biomarkers) in the understanding and
diagnosis of neurodegenerative disorders. The application of imaging biomarkers …