Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed to establish an integrative clinical-genetic framework to elucidate the common frailty factor, the 'F' factor, that captures the systemic vulnerabili...
MOTIVATION: Integrating multi-omics data provides valuable insights into biological processes by capturing information across multiple molecular layers, enabling a comprehensive understanding of complex diseases and driving advancements in precision medicine. However, existing computational methods for multi-omics integration face significant challenges, such as low reliability and poor generaliza...
Microglial cells are key players in maintaining brain homeostasis and responding to pathological conditions. Their multifaceted roles in health and di...
Current Alzheimer's disease therapies offer limited efficacy and are often accompanied by significant side effects, underscoring the urgent need for n...
OBJECTIVE: To develop an artificial intelligence (AI)-aided dual-task gait test model for scalable, high-throughput cognitive impairment screening. DE...
BackgroundAlthough studies have explored tea and coffee in relation to Alzheimer's disease, no century-scale analysis has jointly examined both within...
BackgroundPost-stroke cognitive impairment (PSCI) is a major vascular contributor to dementia, significantly impacting long-term recovery and quality ...
BACKGROUND: Thyroid carcinoma (TC) presents a rising global incidence, with a subset of cases progressing aggressively despite standard therapies. The...
Alzheimer disease (AD) and Postoperative delirium (POD) may share a common mechanism, but their shared genes and potential novel therapeutic targets r...
The European research landscape for developing new diagnostic, preventive, and therapeutic interventions is fraught with challenges. Scarcity of quali...
Dysregulated lipid metabolism drives atherosclerosis (AS). Yacon, an Andean lipid-modulating tuber, exerts anti-AS potential, but mechanisms remain un...
Despite robust preclinical evidence, many clinical trials, including several that targeted the purinergic system, fail to demonstrate efficacy in huma...
BACKGROUND: Early identification of Alzheimer's disease-related cognitive impairment remains challenging, and existing machine learning (ML) models of...
Magnetic resonance imaging (MRI) is widely regarded as the most reliable non-invasive imaging modality for detecting neurological disorders. However, ...
BACKGROUND: Early recognition of Alzheimer's disease (AD) is crucial for timely intervention and delaying disease progression. Electroencephalogram (E...
BACKGROUND: Alzheimer disease (AD) is a progressive neurodegenerative disorder with rapidly growing global prevalence. Early detection is critical for...
This study presents a novel phase-change cooling strategy that synergistically integrates acoustofluidic bubble dynamics with nanoarray-coated micropi...
Community Health Needs Assessments (CHNAs), mandated by the Affordable Care Act for tax-exempt hospitals, represent an underutilized yet rich data sou...
OBJECTIVES: The pathophysiology of idiopathic intracranial hypertension (IIH) is poorly understood and disease-specific biomarkers are lacking. We aim...
PURPOSE: Neurocognitive and endocrine dysfunction are potential complications of cranial irradiation. However, risk factors are poorly understood, imp...