Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
With global population aging and the increasing prevalence of chronic diseases, the traditional reactive medical model, which focuses on post-illness management, is increasingly inadequate for addressing the structural challenges currently facing healthcare systems. With Taiwan now an aging society, the long-term care needs arising from disability, dementia, and multiple comorbidities further unde...
INTRODUCTION: Although tau positron emission tomography (PET) imaging is effective for staging tau pathology, it is limited clinically by cost and availability. Machine learning models based on magnetic resonance imaging (MRI)- and amyloid PET-derived features may serve as useful screening tools for tau pathology. METHODS: Multiple machine learning models were developed to classify tau positivity ...
Sepsis is characterized by potentially fatal organ failure resulting from the host's abnormal response to infection. Due to the complex and rapid prog...
BACKGROUND: Mild cognitive impairment (MCI) represents a clinically critical and heterogeneous syndrome characterized by cognitive decline exceeding n...
BACKGROUND: Although fine particulate matter (PM2.5) has been associated with cognitive dysfunction (CD), the roles of specific PM2.5 components and p...
US healthcare systems are struggling to meet the growing demand for neurological care, particularly in Alzheimer's disease and related dementias. Gene...
BACKGROUND: Hypospadias is a common congenital malformation requiring surgery. Caregivers face substantial perioperative information needs, and large ...
The objective of this study is to demonstrate an end-to-end approach for operationalizing the Findable, Accessible, Interoperable, and Reusable (FAIR)...
BACKGROUND: Large language models (LLMs) are increasingly used by patients and caregivers to obtain medical information. In pediatric acute bacterial ...
BackgroundDementia, including Alzheimer's disease, represents one of the fastest-growing global health challenges. To coordinate research priorities, ...
BackgroundAlzheimer's disease and related dementias (ADRD) place an immense burden on patients, families, and health systems in the United States. Hyp...
BackgroundNeuron loss is a hallmark of neurodegenerative diseases and leads to brain atrophy detectable with magnetic resonance imaging (MRI). Accurat...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Familial AD accounts for less than 1% of cases, while sporadic AD (SAD) accounts...
Alzheimer's disease (AD) is a progressively worsening type of brain disorder that damages the nerve cells. It is marked by the buildup of amyloid-β pl...
Accurate diagnosis and progression prediction of Alzheimer's disease (AD) remain challenging due to the heterogeneous nature of the disease, which inv...
Current dementia diagnostic methods can be costly, invasive, or limited in their ability to distinguish between disorders with overlapping clinical sy...
Early detection of cognitive impairment in assisted living is hindered by time-intensive tools like the Mini-Mental State Examination (MMSE) and the M...
BACKGROUND: AI-enabled chatbots and related conversational systems can facilitate human-computer interaction through natural language, personalization...
BACKGROUND: Generative artificial intelligence (GenAI) tools are widely accessible to the public, who are engaging with them for a wide range of healt...
BACKGROUND AND PURPOSE: Frontotemporal dementia (FTD) is characterized by frontal and anterior temporal lobe atrophy and progressive changes in behavi...