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

Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive
cognitive decline, is the most common form of dementia. Currently, there is no single test that …

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

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

This study introduces a novel deep-learning methodology that is customized to automatically
diagnose Alzheimer's disease (AD) through the analysis of MRI datasets. The process of …

Alzheimer's disease (AD) is the most common cause of dementia, marked by cognitive
decline and memory loss. Recently, machine learning and deep learning techniques have …

Alzheimer's disease is one of the leading causes of death globally, significantly impacting
countless families and communities. In parallel, recent advancements in molecular biology …