Alzheimer's Disease

Eyes Are the Windows to the Soul: Reviewing the Possible Use of the Retina to Indicate Traumatic Brain Injury.

Traumatic brain injury (TBI) induces complex molecular and cellular responses, often leading to vision deterioration and potential mortality. Current objective diagnostic methods are limited, necessitating the development of novel tools to assess disease severity. This review focuses on the retina, a readily approachable part of the central nervous system (CNS), as a potential indicator of TBI. We...

Radiomic and proteomic signatures of body mass index on brain ageing and Alzheimer's-like patterns of brain atrophy.

BACKGROUND: The impact of high body mass index (BMI) states and associated proteomic factors on brain ageing and Alzheimer's disease (AD) remains unclear.

Modeling Brain Aging with Explainable Triamese ViT: Towards Deeper Insights into Autism Disorder.

Machine learning, particularly through advanced imaging techniques such as three-dimensional Magnetic Resonance Imaging (MRI), has significantly impro...

Emerging blood biomarkers in Alzheimer's disease: a proteomic perspective.

Early detection of Alzheimer's disease (AD) remains a formidable clinical challenge, but emerging blood-based assays show promise for identifying at-r...

AI-assisted multi-OMICS analysis reveals new markers for the prediction of AD.

Alzheimer's Disease (AD) is the most prevalent neurodegenerative disorder, characterized by progressive cognitive decline. Early and accurate diagnosi...

Advances in Diagnostic Approaches for Alzheimer's Disease: From Biomarkers to Deep Learning Technology.

Alzheimer's disease (AD) is a devastating neurological disorder that affects humans and is a major contributor to dementia. It is characterized by cog...

Machine Learning for Missing Data Imputation in Alzheimer's Research: Predicting Medial Temporal Lobe Flexibility.

BACKGROUND: Alzheimer's disease (AD) begins years before symptoms appear, making early detection essential. The medial temporal lobe (MTL) is one of t...

Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer's disease.

BACKGROUND: The NeuroArtP3 (NET-2018-12366666) is a multicenter study funded by the Italian Ministry of Health. The aim of the project is to identify ...

Heterogeneity in the association between internet use and dementia among older adults: A machine-learning analysis.

BACKGROUND & AIMS: Internet use among older adults may reduce the risk of dementia, but it remains unknown how the effects vary across individuals. Th...

Computational Risk Stratification of Preclinical Alzheimer's in Younger Adults.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that often begins decades before clinical symptoms manifest. Early detection rem...

Predicting Cognitive Decline in Motoric Cognitive Risk Syndrome Using Machine Learning Approaches.

: Motoric Cognitive Risk Syndrome (MCR), defined by the co-occurrence of subjective cognitive complaints and slow gait, is recognized as a preclinical...

Prediction of mild cognitive impairment using blood multi-omics data.

Mild cognitive impairment (MCI) represents an initial phase of memory or other cognitive function decline and is viewed as an intermediary stage betwe...

Speech-based digital cognitive assessments for detection of mild cognitive impairment: Validation against paper-based neurocognitive assessment scores.

BackgroundCognitive decline in Alzheimer's disease (AD) often includes speech impairments, where subtle changes may precede clinical dementia onset. A...

Translational computerized clinical decision support systems for Alzheimer's disease: A systematic review.

BackgroundAlzheimer's disease (AD), marked by progressive memory loss and cognitive decline, poses diagnostic challenges due to its multifactorial nat...

CDKN1A and EGR1 are key genes for endoplasmic reticulum stress-induced ferroptosis in MASH.

Metabolic dysfunction-associated steatohepatitis (MASH) is a complex liver disease whose pathogenesis involving endoplasmic reticulum (ER) stress and ...

A Convolutional Mixer-Based Deep Learning Network for Alzheimer's Disease Classification from Structural Magnetic Resonance Imaging.

Alzheimer's disease (AD) is a neurodegenerative disorder that severely impairs cognitive function across various age groups, ranging from early to la...

Brain age prediction from MRI scans in neurodegenerative diseases.

PURPOSE OF REVIEW: This review explores the use of brain age estimation from MRI scans as a biomarker of brain health. With disorders like Alzheimer's...

When is imaging needed to assess the response to treatment in cardiac amyloidosis.

PURPOSE OF REVIEW: Cardiac amyloidosis is characterized by systolic and diastolic abnormalities due to deposition of amyloid fibril within the myocard...

A Novel Dynamic Neural Network for Heterogeneity-Aware Structural Brain Network Exploration and Alzheimer's Disease Diagnosis.

Heterogeneity is a fundamental characteristic of brain diseases, distinguished by variability not only in brain atrophy but also in the complexity of ...

Identification of shared mechanisms between Alzheimer's disease and atherosclerosis by integrated bioinformatics analysis.

Alzheimer's disease (AD) and atherosclerosis (AS) are two interacting diseases mostly affecting aged adults. AD is characterized by the deposition of ...