AIMC Topic: Cognitive Dysfunction
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Developing a prediction model for cognitive impairment in older adults following critical illness.
BMC geriatrics
Nov 29, 2024
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...
BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.
Neural networks : the official journal of the International Neural Network Society
Nov 26, 2024
The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological cond...
Deep-learning assessment of hippocampal magnetic susceptibility in Alzheimer's disease.
Journal of Alzheimer's disease : JAD
Nov 25, 2024
BACKGROUND: Quantitative susceptibility mapping (QSM) is pivotal for analyzing neurodegenerative diseases. However, accurate hippocampal segmentation remains a challenge.
Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes.
Journal of Alzheimer's disease : JAD
Nov 25, 2024
BACKGROUND: Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atrophy. Elucidating the relationships between local morphometric changes and disease status for early diagnosis could be aided by machine learning algori...
Graph Convolutional Network for AD and MCI Diagnosis Utilizing Peripheral DNA Methylation: Réseau de neurones en graphes pour le diagnostic de la MA et du TCL à l'aide de la méthylation de l'ADN périphérique.
Canadian journal of psychiatry. Revue canadienne de psychiatrie
Nov 25, 2024
OBJECTIVE: Blood DNA methylation (DNAm) alterations have been widely reported in the onset and progression of mild cognitive impairment (MCI) and Alzheimer's disease (AD); however, DNAm is underutilized as a diagnostic biomarker for these diseases. W...
Predicting the cognitive impairment with multimodal ophthalmic imaging and artificial neural network for community screening.
The British journal of ophthalmology
Nov 22, 2024
BACKGROUND/AIMS: To investigate the comprehensive prediction ability for cognitive impairment in a general elder population using the combination of the multimodal ophthalmic imaging and artificial neural networks.
Multiclass classification of Alzheimer's disease prodromal stages using sequential feature embeddings and regularized multikernel support vector machine.
NeuroImage
Nov 19, 2024
The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is crucial for early treatment interventions. However, the heterogeneity of MCI data samples poses a cha...
A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.
Cells
Nov 19, 2024
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...
Application and effectiveness of adaptive AI in elderly healthcare.
Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
Nov 13, 2024
BACKGROUND: In addressing elderly healthcare issues, cognitive impairment can cause significant disruptions in daily life and may potentially develop into dementia. Thus, finding ways to delay the progression of cognitive impairment is a critical iss...
Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning.
ACS chemical neuroscience
Nov 13, 2024
Accurate and early disease detection is crucial for improving patient care, but traditional diagnostic methods often fail to identify diseases in their early stages, leading to delayed treatment outcomes. Early diagnosis using blood derivatives as a ...
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