Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
INTRODUCTION: Spontaneous speech is commonly disrupted in persons with Alzheimer's disease (AD) and/or Alzheimer's clinical syndrome (ACS). Importantly, different aspects of speech (e.g. formulaic versus more novel or flexible speech) place different demands on distinct cognitive systems. Formulaic language may rely on automatized procedural processes, while more novel or diverse speech requires m...
BACKGROUND: Carotid plaque instability is a major determinant of ischemic stroke and is characterized by heightened inflammation and structural remodeling of the vessel wall. Although macrophages and vascular smooth muscle cells (VSMCs) are central to plaque vulnerability, the mechanisms coordinating immune activation with vascular remodeling remain incompletely understood. METHODS: Bulk transcrip...
INTRODUCTION: Medical tourism (MT) caregiving companions are often expected to navigate unfamiliar healthcare systems, manage high-stress situations, ...
OBJECTIVE: Family caregivers of persons with dementia experience grief as the care recipients' dementia advances. Here, we explore how various interpe...
The brain age gap (BAG), the difference between magnetic resonance imaging-predicted brain age and chronological age, is a proposed marker of neurobio...
Accurately perceiving object softness remains challenging for tactile sensors, as current approaches estimate Young's modulus from object deformation ...
BACKGROUND: Cerebral small vessel disease (CSVD) is a major contributor to vascular dementia. Given the absence of effective treatments, the developme...
OBJECTIVES: This study aimed to develop a super lightweight deep learning model for brain age estimation using structural MRI, enabling accurate age e...
BACKGROUND: Pediatric severe traumatic brain injury (sTBI) remains a leading cause of death and long-term disability, yet its molecular characterizati...
Early hospital readmission in multimorbid patients remains a major clinical challenge. Although risk stratification tools are widely used, predictive ...
Dynamic effective connectivity (dEC) analysis provides an approach for revealing the causal mechanism of information transmission in human brain. Howe...
Accurate identification of neurological disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and Autism Spectrum Disorder (ASD) is ch...
This research letter reports the development and preliminary user testing of MusicAlzheimer, an artificial intelligence-driven digital music therapy p...
Alzheimer's disease (AD) presents considerable heterogeneity in disease risk and outcomes, posing a major challenge for effective therapeutic developm...
Alzheimer's Disease (AD) has traditionally been approached through a biomedical lens, focusing on neurodegenerative markers such as amyloid-β plaques ...
Secretory Glutaminyl Cyclase (sQC) catalyzes the formation of pyroglutamate amyloid-β (pE-Aβ), a highly aggregation-prone and neurotoxic species. In t...
Clinical implementation of neurofilament light chain (NfL), a biomarker of neurodegeneration, remains challenging due to absence of reliable cutoffs a...
INTRODUCTION: Plasma proteins reflect the combined influence of both internal and external factors, making proteomics-based aging clocks a promising a...
Dementia, particularly Alzheimer's disease (AD), is a growing concern in aging populations, with mild cognitive impairment (MCI) frequently progressin...
Accurate detection of Mild Cognitive Impairment (MCI) is critical for timely intervention and for slowing progression to Alzheimer's disease. Electroe...