Background Clinical prediction is integral to modern healthcare, leveraging current and
historical medical data to forecast health outcomes. The integration of Artificial Intelligence …

Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research
and clinical practice due to its complex etiology and progressive nature. The integration of …

Artificial intelligence (AI) is rapidly transforming healthcare, and one of its most promising
applications is in the diagnosis and treatment of diseases. AI algorithms can analyze vast …

The application of artificial intelligence (AI) in neurology is a growing field offering
opportunities to improve accuracy of diagnosis and treatment of complicated neuronal …

Alzheimer's disease (AD) is currently constrained by limited clinical treatment options. The
initial pathophysiological event, which can be traced back to decades before the clinical …

Alzheimer's disease (AD) is a age-related neurodegenerative disease and is a major public
health concern both in Texas, US and Worldwide. This neurodegenerative disease is mainly …

The advent of eXplainable Artificial Intelligence (XAI) has revolutionized the way human
experts, especially from non-computational domains, approach artificial intelligence; this is …

Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology,
significantly impacting the diagnosis and treatment of neurological disorders. Recent …

Alzheimer's disease (AD) progressively impairs the memory and thinking skills of patients,
resulting in a significant global economic and social burden each year. However, diagnosis …

Abstract Early detection of Mild Cognitive Impairment (MCI) leads to early interventions to
slow the progression from MCI into dementia. Deep Learning (DL) algorithms could help …