Alzheimer's Disease

Physicochemical mechanisms of aggregation and fibril formation of α-synuclein and apolipoprotein A-I.

Deposition and accumulation of amyloid fibrils is a hallmark of a group of diseases called amyloidosis and neurodegenerative disorders. Although polypeptides potentially have a fibril-forming propensity, native proteins have evolved into proper functional conformations to avoid aggregation and fibril formation. Understanding the mechanism for regulation of fibril formation of native proteins provi...

Assess Alzheimer's Disease via Plasma Extracellular Vesicle-derived mRNA.

Alzheimer's disease (AD), the most prevalent neurodegenerative disorder globally, has emerged as a significant health concern, particularly due to the increasing aging population. Recently, it has been revealed that extracellular vesicles (EVs) originating from neurons play a critical role in AD pathogenesis and progression. These neuronal EVs can cross the blood-brain barrier and enter peripheral...

Using Generative Artificial Intelligence to Classify Primary Progressive Aphasia from Connected Speech.

Neurodegenerative dementia syndromes, such as Primary Progressive Aphasias (PPA), have traditionally been diagnosed based in part on verbal and nonver...

Deep learning applications in vascular dementia using neuroimaging.

PURPOSE OF REVIEW: Vascular dementia (VaD) is the second common cause of dementia after Alzheimer's disease, and deep learning has emerged as a critic...

Brain age prediction using combined deep convolutional neural network and multi-layer perceptron algorithms.

The clinical applications of brain age prediction have expanded, particularly in anticipating the onset and prognosis of various neurodegenerative dis...

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data.

Large omics datasets are becoming increasingly available for research into human health. This paper presents DeepOmicsAE, a workflow optimized for the...

A deep learning model for Alzheimer's disease diagnosis based on patient clinical records.

BACKGROUND: Dementia, with Alzheimer's disease (AD) being the most common type of this neurodegenerative disease, is an under-diagnosed health problem...

EstimATTR: A Simplified, Machine-Learning-Based Tool to Predict the Risk of Wild-Type Transthyretin Amyloid Cardiomyopathy.

BACKGROUND: Wild-type transthyretin amyloid cardiomyopathy (ATTRwt-CM), an increasingly recognized cause of heart failure (HF), often remains undiagno...

A deep learning model for the detection of various dementia and MCI pathologies based on resting-state electroencephalography data: A retrospective multicentre study.

Dementia and mild cognitive impairment (MCI) represent significant health challenges in an aging population. As the search for noninvasive, precise an...

Classifying Alzheimer's disease and normal subjects using machine learning techniques and genetic-environmental features.

BACKGROUND: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANN...

A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer's Disease using MRI Images.

Recently, the early diagnosis of Alzheimer's disease has gained major attention due to the growing prevalence of the disease and the resulting costs i...

Editorial: Network science approaches to risk assessment of mental disorders and dementia.

Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study.

: While Enterobacteriaceae bacteria are commonly found in the healthy human gut, their colonization of other body parts can potentially evolve into se...

Assessment of systemic inflammation following oral calcium supplementation in healthy postpartum multiparous dairy cows-A randomized controlled trial.

Around parturition, dairy cows inevitably and perhaps necessarily experience some degree of systemic inflammation, but when excessive or dysregulated,...

Cognitive decline assessment using semantic linguistic content and transformer deep learning architecture.

BACKGROUND: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities indepen...

Role of environmental specificity in CASP results.

BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence te...

Classification of helical polymers with deep-learning language models.

Many macromolecules in biological systems exist in the form of helical polymers. However, the inherent polymorphism and heterogeneity of samples compl...

Individualized Assessment of Brain Aβ Deposition With fMRI Using Deep Learning.

PET-based Alzheimer's disease (AD) assessment has many limitations in large-scale screening. Non-invasive techniques such as resting-state functional ...

Deep Learning-Based Ensembling Technique to Classify Alzheimer's Disease Stages Using Functional MRI.

The major issue faced by elderly people in society is the loss of memory, difficulty learning new things, and poor judgment. This is due to damage to ...

Applications of artificial intelligence in dementia.

The recent evolution of artificial intelligence (AI) can be considered life-changing. In particular, there is great interest in emerging hot topics in...