Alzheimer's Disease

Chronological Diagnostic Algorithm Predicting Neuropathology in Parkinsonism.

OBJECTIVE: Pre-mortem diagnosis of parkinsonism is often challenging due to atypical presentations, ...

Autophagy-exosome crosstalk in neurodegeneration: Mechanisms and therapeutic opportunities.

Neurodegenerative diseases (NDs), including Alzheimer's, Parkinson's, Huntington's, amyotrophic late...

Estimating cognitive function score from mild cognitive impairment to moderate dementia using a hybrid model combining plasma biomarkers with electroencephalogram signal.

BackgroundPredicting cognitive function across dementia stages remains challenging. Plasma biomarker...

Integrated network toxicology and computational profiling of acetyl tributyl citrate-related mechanisms in Alzheimer's disease.

BackgroundAcetyl tributyl citrate (ATBC), an eco-friendly plasticizer, exhibits poorly characterized...

Causal Discovery in Observational Medical Research: Scoping Review.

BACKGROUND: Observational data are fundamental to medical research but present formidable challenges...

Predictive modeling for early diagnosis of dementia using sequential data analysis and data mining.

Dementia, a progressively debilitating neurodegenerative disorder, poses a growing challenge to glob...

Machine-learning prediction and risk stratification of 12-month cognitive decline in Alzheimer's disease using routine clinical and MRI data.

Early identification of patients with Alzheimer's disease (AD) who will experience near-term cogniti...

Identifying serum amino acid as biomarkers of gestational diabetes mellitus in second-trimester among Chinese pregnant women: a machine learning-based cross-sectional study.

BACKGROUND: Levels of plasma branched-chain and aromatic amino acids in pregnancy have been associat...

Improved polygenic risk prediction for alzheimer's disease and related dementias using deep learning: age and APOE-stratified analysis.

Early detection of Alzheimer's disease based on leveraging multimodal features of the clock drawing test.

BackgroundAlthough multi-task handwriting analysis has the potential to improve early detection of A...

Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007-2022).

BackgroundAlzheimer's disease (AD) patients frequently present to emergency departments (EDs) with c...

Exploratory analysis of the associations of the brain age gap with cognitive function and amyloid-β accumulation: participants selection based on metabolic and physiological blood markers.

The brain age gap (BAG) is defined as the difference between brain age estimated from MRI using arti...

Amyloid PET quantification with deep learning segmentation models without MRI.

Establishing a relationship between iron-based blood measures and structural brain changes using neural networks in UK Biobank.

BACKGROUND: Disturbance of iron homeostasis in both the brain and blood is linked to cognitive impai...

Dual modal data-driven virtual reality-based mild cognitive Impairment assessment using MCIformer.

BACKGROUND: Mild Cognitive Impairment (MCI) assessment is critical for identifying cognitive decline...

HIF3A-mediated aberrant activation of TXNIP promotes Alzheimer's disease progression.

Oxidative stress (OS) is a hallmark of Alzheimer's disease (AD), yet the cell type-specific mechanis...

Clinical and pathologic correlations of machine learning quantification of Aβ deposits across 3 brain regions of decedents with Alzheimer disease.

Machine learning enables scalable quantification of neuropathology, offering deeper phenotyping of A...

Fusing serum peptidome profiles with clinical variables via machine learning for pulmonary embolism risk assessment.

Pulmonary embolism (PE) remains a life-threatening cardiovascular emergency that requires timely and...

Correction to "Design of Tau Aggregation Inhibitors Using Iterative Machine Learning and a Polymorph-Specific Brain-Seeded Fibril Amplification Assay".

EENet-RLA: An Explainable Prediction Learning Framework for Alzheimer's Disease Classification from EEG Signals.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting millions worldwide. Ele...

Resource-stratified machine learning framework for cognitive status classification and mild cognitive impairment to dementia progression prediction.