Dementia

Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer's disease and related disorders. Ultra-high resolution postmortem MRI can help identify regions that fall outside the diagnostic sampling criteria for additional histopathologic evaluation. However,...

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.

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...

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...

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...

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 ...

Random field image representations speed up binary discrimination of brain scans and estimate a phenotype glioblastoma cancer cell model.

MRI brain scans alone are not a definitive measure of dementia. Deep-learning algorithms (DLA) and professional human opinion are necessary for diagno...

A pathway-informed disease-related gene identification approach and its application to screen novel risk genes for Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a severe neurodegenerative disorder, yet its molecular mechanisms remain incompletely understood. It is known ...

Machine learning applied to mild cognitive impairment: bibliometric and visual analysis from 2015 to 2024.

BACKGROUND: At present, the world is in the background of severe aging population challenges. Mild cognitive impairment (MCI), an intermediate state b...

Functional MRI Analysis of Cortical Regions to Distinguish Lewy Body Dementia From Alzheimer's Disease.

OBJECTIVE: Cortical regions such as parietal area H (PH) and the fundus of the superior temporal sulcus (FST) are involved in higher visual function a...

Layer-Specific Colocalization of Microglia with Amyloid Plaques in the Middle Temporal Gyrus Predicts Cognitive Decline in Alzheimer's Disease.

Alzheimer's disease (AD), the most common form of dementia, is marked by cognitive decline and amyloid-beta (Aβ) plaque deposition in the brain. Micro...