AIMC Topic: Cognitive Dysfunction

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Alterations of multilayer network correlated with cognitive impairment and gene expression profiles in children with idiopathic generalized epilepsy.

Scientific reports
This study investigated dynamic brain network changes and their genetic correlations in children with idiopathic generalized epilepsy (IGE). We included 26 children with IGE and 35 healthy controls, all participants underwent resting-state functional...

Aging as an active player in Alzheimer's disease classification: Insights from feature selection in BrainAge models.

NeuroImage
BACKGROUND: BrainAge models estimate the biological age of the brain using neuroimaging or clinical features, making them promising tools for studying neurodegenerative diseases like Alzheimer's disease. However, the reliance of BrainAge models on ne...

Clinical application of 3D reconstruction and accurate volume measurement of white matter in patients with cognitive dysfunction.

Scientific reports
To quantitatively measure the volume of white matter hyperintensities (WMHs) in different parts of the brain in patients with different types of cognitive function and analyze the relationship between WMH volume and cognitive function to obtain a thr...

Machine learning-based stratification of mild cognitive impairment in Parkinson's disease: a multicenter cross-sectional analysis.

BMC medical informatics and decision making
BACKGROUND: Cognitive impairment is a prominent non-motor manifestation of Parkinson's disease (PD) and is associated with reduced quality of life, increased mortality, and higher healthcare utilization. We aimed to develop and externally validate a ...

A radiomics model predicts progression from mild cognitive impairment to alzheimer's disease using structural MRI.

Scientific reports
The aim of this study is to build and validate a model based on structural magnetic resonance imaging (sMRI) to predict the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD). A total of 343 patients with MCI were selected fro...

Machine learning-based estimation of the mild cognitive impairment stage using multimodal physical and behavioral measures.

Scientific reports
Mild cognitive impairment (MCI) is a prodromal stage of dementia, and its early detection is critical for improving clinical outcomes. However, current diagnostic tools such as brain magnetic resonance imaging (MRI) and neuropsychological testing hav...

An ensemble model based on transfer learning for the early detection of Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the gradual decline in cognitive functions, particularly memory and reasoning. Early detection, especially during cognitive impairment (MCI) stage, is crucial for t...

An optimized hybrid deep learning model to detect Alzheimer disease.

Scientific reports
Alzheimer's is a serious neurodegenerative disease that requires early detection for effective intervention. Traditional methods often struggle with accurately identifying the early stages, such as mild cognitive impairment (MCI), due to limitations ...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...