Geriatrics

Alzheimer's Disease

Latest AI and machine learning research in alzheimer's disease for healthcare professionals.

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Geriatrics Subcategories: Alzheimer's Disease Medicare
Showing 2561-2580 of 14,181 articles

An Indicator Cell Assay-based Multivariate Blood Test for Early Detection of Alzheimer’s Disease

The indicator cell assay platform (iCAP) is a novel next-generation approach for blood-based diagnostics that uses standardized cells as biosensors to amplify weak disease signals in blood. We developed an Alzheimer’s disease iCAP (AD-iCAP) for early detection at the mild cognitive impairment/mild dementia stages. To develop the assay, patient plasma is incubated with standardized neurons, which t...

Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive decline

Sleep disturbances and altered circadian rhythms are well-documented in both physiological and biological studies of dementia. The exact causal relationship remains unclear. Several other long-term health conditions may also influence sleep patterns. Examining sleep patterns in relation to chronological ageing and the variations and progression of dementia, considering factors such as age, sex, an...

DualAlign: Generating Clinically Grounded Synthetic Data

Synthetic clinical data are increasingly important for advancing AI in healthcare, given strict privacy constraints on real-world EHRs, limited availa...

An Unsupervised XAI Framework for Dementia Detection with Context Enrichment

Explainable Artificial Intelligence (XAI) methods enhance the diagnostic efficiency of clinical decision support systems by making the predictions of ...

Identification of Key Genes Governing the Effects of Physical Activity on Ferroptosis in Alzheimer’s Disease Patients: A Machine Learning-Based Study

Disrupted brain iron metabolism and activated ferroptosis during ageing constitute significant precursors to neurodegenerative diseases. However, whet...

Robust Disease Prognosis via Diagnostic Knowledge Preservation: A Sequential Learning Approach

Accurate disease prognosis is essential for patient care but is often hindered by the lack of long-term data. This study explores deep learning traini...

Dementia Risk and Machine Learning-Derived Brain Age Index from Sleep Electroencephalography: A Pooled Cohort Analysis of Over 7,000 Individuals Across Five Community Cohorts

Sleep electroencephalographic (EEG) microstructures are closely related to cognition and undergo age-dependent changes. However, their multidimensiona...

Plasma Proteomics Linking Primary and Secondary diseases: Insights into Molecular Mediation from UK Biobank Data

Diabetes, hypertension, and dyslipidemia are major risk factors for cardiovascular (CVD), cerebral, and renal diseases (RD). However, the underlying m...

Incidentally discovered Covert Cerebrovascular Disease by CT versus MRI: Agreement and Prognostic Value for Stroke and Dementia in a Large Real-World Cohort

Covert cerebrovascular disease (CCD), comprising covert brain infarction (CBI) and white matter disease (WMD), is common in older adults and linked to...

A randomized clinical trial reveals effects of mindfulness and slow breathing on plasma amyloid beta levels

Prior research suggests that meditation may slow brain aging and reduce the risk of Alzheimer’s disease (AD). However, we lack research systematically...

Predicting Future Brain Atrophy Based on Longitudinal MRI

Neuron loss is a key feature of neurodegenerative diseases often leading to brain atrophy detectable through magnetic resonance imaging (MRI). Various...

A Self-Explainable Dynamic Risk Monitoring Framework for Predicting Alzheimer’s Disease and Related Dementias

Alzheimer’s Disease and Related Dementias (ADRD) affect millions worldwide and can begin over a decade before symptoms appear. ADRD are generally irre...

Early Detection of Cognitive Decline in Parkinson’s Disease Using Natural Language Processing of Clinical Notes: A Systematic Review and Meta-Analysis Protocol

Cognitive decline affects approximately 40% of Parkinson’s disease (PD) patients within 10 years of diagnosis, progressing to dementia in 80% of patie...

Cerebrospinal fluid proteomics for predictive assessment of Alzheimer’s Disease risk

Alzheimer’s disease (AD) involves early molecular changes beyond amyloid-β (Aβ) and tau, that create heterogeneous disease biology, giving rise to var...

Deep learning aging marker from retinal images unveils sex-specific clinical and genetic signatures

Retinal fundus images offer a non-invasive window into systemic aging. Here, we fine-tuned a foundation model (RETFound) to predict chronological age ...

ALTARN: A Tabular Residual Neural Network for Alzheimer’s Disease Classification and Prediction

Early and accurate prediction of Alzheimer’s disease (AD) from accessible clinical data remains a significant challenge in healthcare. This study prop...

Speech Acoustic Markers Detect APOE-ε4 Carrier Status in Cognitively Healthy Individuals

APOE-ε4, the strongest genetic risk factor for Alzheimer’s disease (AD), is linked to early motor vulnerability, including subtle speech control chang...

Neuro: Machine Learning Optimized to Detect Neurodegenerative Diseases Pilot Study

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that primarily affects cognitive function. Early detection is a crucial factor in...

Predicting future cognitive impairment in preclinical Alzheimer’s disease using multimodal imaging: a multisite machine learning study

Predicting the likelihood of developing Alzheimer’s disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...

Alzheimer’s Disease Stage Classification via Multimodal CNN on EEG Spectrograms and Cube-Drawing Images

Clinicians currently lack reliable tools to determine, at the point of mild cognitive impairment (MCI), which individuals will progress to Alzheimer’s...

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