Alzheimer's Disease

Predicting Cognition and Affective Changes in Newly Diagnosed Parkinson's Disease Through Longitudinal Data-Driven Clustering.

Background: Although primarily characterised as a motor disorder, Parkinson's Disease (PD) also presents with non-motor symptoms, including cognitive decline and affective dysfunction, which are major predictors of quality of life and mortality for individuals. However, factors associated with these non-motor symptom trajectories remain under-characterised. Purpose: This study aimed to investigate...

Fingernail-based metabolomics reveals a stepwise decline in dodecanoic acid associated with Alzheimer's disease progression.

BACKGROUND: Fingernail metabolomics provides a novel, non-invasive platform that captures long-term biochemical fluctuations for identifying reliable biomarkers for dementia and mild cognitive impairment (MCI) due to Alzheimer's disease (AD). METHODS: A total of 199 participants were enrolled and stratified according to Clinical Dementia Rating (CDR) scores (0, 0.5, 1, 2, and 3). Fingernail clippi...

Integrating Time and Frequency Domain Features of fMRI Time Series for Alzheimer's Disease Classification Using Graph Neural Networks.

Accurate and early diagnosis of Alzheimer's Disease (AD) is crucial for timely interventions and treatment advancement. Functional Magnetic Resonance ...

AI fragment based optimization of saffron and chamomile phytochemicals as aryl hydrocarbon receptor inhibitors for dementia therapy an integrated computational approach.

Dementia represents a rapidly rising global health challenge as a progressive neurodegenerative disease with few options for disease-modifyingtreatmen...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases (NDDs) have highlighted microglial dysfunction as...

Brain region localization: a rapid Parkinson's disease detection method based on EEG signals.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder worldwide, often progressing to mild cognitive impairment (MCI) and dementia. Clini...

Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.

The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties over time. Currently, there is no remedy for this ill...

Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.

Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing significant challenges in providing appropriate car...

Structural and pragmatic language skills in school-age children relate to resting state functional connectivity.

Language difficulties are common in school-age children but their etiology is often unknown. Although neural underpinnings of language have been well-...

Speech production as an artificial intelligence-based 'process' measure of cognition sensitive to mild cognitive impairment and Alzheimer's disease.

Process scores in neuropsychological tests add incremental validity for detecting non-normative cognitive aging trajectories. However, process scores...

EEG Signal Analysis for the Classification of Alzheimer's and Frontotemporal Dementia: A Novel Approach Using Artificial Neural Networks and Cross-Entropy Techniques.

Dementia, a neurological disorder, can cause cognitive decline due to damage to the brain. Our study aims to contribute to the development of computer...

Virtual Hydrolysis-Based Screening of Wheat-Derived DPP-IV Inhibitory Peptides: A Mechanistic Analysis Integrating Cell Experiments and Molecular Dynamics Simulations.

Dipeptidyl peptidase-IV (DPP-IV) inhibitors play a critical role in the treatment of diabetes and metabolic diseases. This study combines computationa...

Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer's disease diagnosis.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder marked by neuronal loss, leading to cognitive and behavioral decline. With the ag...

Biomimetic Analysis of Neurotransmitters for Disease Diagnosis through Light-Driven Nanozyme Sensor Array and Machine Learning.

Neurological diseases, including Alzheimer's disease, Parkinson's disease, and multiple sclerosis, pose a significant global health challenge due to t...

Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis.

BACKGROUND: Delays in the diagnosis of transthyretin amyloid cardiomyopathy (ATTR-CM) contribute to the significant morbidity of the condition, especi...

Machine-learning based strategy identifies a robust protein biomarker panel for Alzheimer's disease in cerebrospinal fluid.

BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current biomarkers for its classification and diagnosis, nece...

BrainAGE latent representation clustering is associated with longitudinal disease progression in early-onset Alzheimer's disease.

INTRODUCTION: Early-onset Alzheimer's disease (EOAD) population is a clinically, genetically and pathologically heterogeneous condition. Identifying b...

Transformer attention-based neural network for cognitive score estimation from sMRI data.

Accurately predicting cognitive scores based on structural MRI holds significant clinical value for understanding the pathological stages of dementia ...

Using Machine Learning to Predict Treatment Outcome in a Concatenated Dataset of Youth Anxiety Treatments.

Machine Learning (ML) is a promising approach for predicting outcomes of youth anxiety treatments. To this end, data from nine randomized controlled t...

Artificial Intelligence in Diagnosis and Prognosis of Cognitive Impairment in Parkinson's Disease.

Parkinson's disease (PD), a progressive neurodegenerative disorder, affects millions globally, with cognitive impairment as a significant non-motor co...