Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
Early detection of neurodegeneration remains a critical clinical challenge. This study investigates whether sleep EEG signal criticality, quantified via Multifractal Detrended Fluctuation Analysis (MFDFA), serves as a non-invasive biomarker for future cognitive decline. We analyzed longitudinal data from the National Sleep Research Resource (NSRR) Study of Osteoporotic Fractures (SOF) cohort, comp...
Alzheimer's disease (AD) progression is highly heterogeneous and is typically observed through sparse and irregular longitudinal data, posing challenges for prediction and personalised monitoring. Existing machine learning approaches have improved AD prediction using multimodal data, yet often focus on static classification or cohort-level risk estimation, providing limited support for subject-spe...
Despite substantial interest in how neural systems recover over time after acute neurological events, there is a dearth of longitudinal assessment fro...
Background: Machine learning models trained on population health surveys offer scalable tools for cardiovascular screening, but recurring methodologic...
The development of multilingual Alzheimer's Disease Dementia (AD) detection models presents significant challenges due to the resource-intensive and t...
Neurodegenerative disorders such as Alzheimer's disease exhibit highly organized patterns of regional brain vulnerability, yet the biological mechanis...
Advances in computational modeling, neuroimaging, and artificial intelligence are revolutionizing the modeling of neurological disorders for improved ...
Background: Cognitive assessments are sparsely documented in electronic health records (EHRs), limiting scalable detection of cognitive worsening in r...
Objective: Alzheimer's disease (AD) is a leading cause of death and disability, and treatment options for Alzheimer's disease and related dementias (A...
Lewy body dementia (LBD), which encompasses Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB), lacks established biofluid markers...
Vocal biomarkers, encompassing voice and speech, have largely been developed for individual conditions in isolation, limiting their generalizability a...
Background: The biomedical literature is expanding at an unprecedented rate, with over 4,000 new articles indexed on PubMed each day. Clinicians and r...
Objective: To systematically evaluate pathway-informed polygenic risk score (PRS) strategies and determine which approaches most effectively leverage ...
Spousal caregivers of individuals with Alzheimers disease and related dementias frequently experience elevated perceived stress, caregiver burden, and...
We trained a self-configuring nnU-Net model for CMB segmentation in a heterogeneous multicenter sample (n=264), including 1.5T and 3T field strengths,...
Cells that store lipids for other cells or organs can contain ''giant'' or large lipid droplets (LLDs) greater than 2 m in diameter. In this study, hu...
Confirming Alzheimer's disease (AD) typically relies on positron emission tomography (PET), which remains costly and invasive, motivating the use of s...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, an...
In biomedical and neurodegenerative disorders, accurate and early disease identification remains challenging due to the scarcity of labeled data and t...
Ligand binding to intrinsically disordered proteins resists description in terms of conventional binding pockets, yet it can be analysed as a dynamic ...