Alzheimer's Disease

Addressing disparities in transthyretin amyloid cardiomyopathy: A systematic review of artificial intelligence in the early identification to improve patient outcomes.

BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) remains substantially underdiagnosed among Black patient populations. When applied to non-invasive diagnostic and screening techniques, artificial intelligence (AI) can aid in the early detection of subtle patterns indicative of transthyretin amyloid cardiomyopathy (ATTR-CM), potentially before clinical symptoms appear. This systematic rev...

Corrigendum to "Enhancing dementia risk prediction with heart rate and machine learning in the Canadian Longitudinal Study on Aging".

Enriched resting-state EEG prediction of cognitive decline in prodromal Alzheimer's disease: a machine-learning approach.

OBJECTIVE: We evaluated the accuracy of standard machine learning (ML) algorithms in predicting 1-year cognitive decline in Alzheimer's disease patien...

Machine-learning approach on echocardiography to improve the detection of transthyretin amyloid cardiomyopathy: GRAAL algorithm.

AIMS: Transthyretin amyloid cardiomyopathy (ATTR-CM) is an increasingly recognized cause of heart failure, yet detection remains challenging due to it...

Ultrastructural Evidence of Altered Dendritic Morphology in the Prefrontal Cortex of Alzheimer's Model Rats.

Alzheimer's disease (AD) is a neurodegenerative disorder with synaptic pathology as a core theme in aging-related research. Conventional imaging and l...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.

INTRODUCTION: Alzheimer's Disease (AD) is among the most prevalent neurodegenerative disorders globally, yet effective early diagnostic strategies rem...

Emerging Roles of Small-molecule Derivatives in Modulating Neurodegenerative Pathways: From Molecular Targets to Therapeutic Applications.

Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease involve progress...

Reimagining Brain Drug Delivery: Mechanistic and Translational Advances in Carbon Nanotube Nanomedicine.

Neurological and neurodegenerative disorders (NDDs) present ongoing therapeutic challenges attributed to the structural complexity of the central nerv...

Multimodal biomarker AI techniques for early neurocognitive disorder diagnosis: A systematic review.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and related dementias remains challenging because no single biomarker sufficiently captures th...

Molecular mechanisms of exercise-induced improvements in Alzheimer's disease: a focus on lipid homeostasis.

Alzheimer's disease (AD) is the most prevalent type of dementia, and its pathophysiological mechanisms involve multiple factors, including genomic fac...

Concussion pathophysiology: From biomechanical insult to clinical phenotype - or is injury truly the beginning?

Mild traumatic brain injury (mTBI) is associated with substantial morbidity worldwide. Emerging evidence demonstrates that both impact- and blast-rela...

Mitochondrial dysfunction and programmed cell death in Alzheimer's disease: A retrospective bioinformatics study.

Alzheimer's disease (AD) is a major cause of dementia, and this paper explores the unclear roles of mitochondrial dysfunction and programmed cell deat...

Corrigendum to: A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis.

In the originally published article entitled "A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis", published in "Curr...

5-Hydroxymethylcytosine profiles in circulating cell-free DNA serve as potential biomarkers for diagnosis and classification of adenomyosis.

BACKGROUND: Adenomyosis diagnosis and classification relies primarily on magnetic resonance imaging or pathological examination. Liquid biopsy has bee...

Integrating NMR Restraints into Coarse-Grained Simulations: Toward Accurate Conformational Ensembles of Complex Protein Systems.

Structural dynamics play critical roles for the biological activity of protein molecules. Characterizing the inherent conformational landscapes of the...

Early cognitive screening for individuals on the dementia continuum: A novel approach amid current trends.

Mild cognitive impairment (MCI) is a critical transitional stage between normal aging and dementia that remains challenging to detect. Many traditiona...

Financial Burden in Adults With Chronic Illness in Switzerland: A Secondary Analysis of Qualitative Interviews Using Natural Language Processing and Topic Modeling.

BACKGROUND: Chronic illness may cause a financial burden that affects patients, their caregivers, and families. While international research, mostly f...

Explainable artificial intelligence for early Alzheimer's diagnosis using enhanced grey relational features and multimodal data.

Alzheimer's disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of...

Deep survival modelling to predict future cognitive impairment in unimpaired adults.

BACKGROUND: Predicting Alzheimer's disease (AD)-related cognitive impairment (CI) among cognitively normal (CN) adults enables meaningful disease modi...