AIMC Topic: Cognitive Dysfunction
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Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability.
BMC public health
Jun 2, 2025
BACKGROUND: Mild Cognitive Impairment (MCI) is a critical transitional stage between normal aging and Alzheimer's disease, and its early identification is essential for delaying disease progression.
Utility of artificial intelligence-based conversation voice analysis for detecting cognitive decline.
PloS one
Jun 2, 2025
Recent developments in artificial intelligence (AI) have introduced new technologies that can aid in detecting cognitive decline. This study developed a voice-based AI model that screens for cognitive decline using only a short conversational voice s...
A preliminary study of the reliability and validity of the Uyghur version of the NUCOG cognitive screening application.
BMC neurology
May 29, 2025
INTRODUCTION: Technological advances and artificial intelligence now make it feasible to administer cognitive assessments on touch-screen devices. The aim of this study is to develop a Uyghur version of the NUCOG cognitive screening application and e...
The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging.
BMC medical imaging
May 22, 2025
BACKGROUND: White matter hyperintensities (WMHs) are closely associated with cognitive frailty (CF). This study aims to explore the potential diagnostic value of WMHs for CF based on radiomics approaches, thereby providing a novel methodology for the...
Brain metabolic imaging-based model identifies cognitive stability in prodromal Alzheimer's disease.
Scientific reports
May 17, 2025
The recent approval of anti-amyloid pharmaceuticals for the treatment of Alzheimer's disease (AD) has created a pressing need for the ability to accurately identify optimal candidates for anti-amyloid therapy, specifically those with evidence for inc...
EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.
Scientific reports
May 7, 2025
In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and t...
Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.
American journal of Alzheimer's disease and other dementias
May 5, 2025
To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a...
Automated Quantification of Cerebral Microbleeds in SWI: Association with Vascular Risk Factors, White Matter Hyperintensity Burden, and Cognitive Function.
AJNR. American journal of neuroradiology
May 2, 2025
BACKGROUND AND PURPOSE: The amount and distribution of cerebral microbleeds (CMB) are important risk factors for cognitive impairment. Our objective was to train and validate a deep learning (DL)-based segmentation model for cerebral microbleeds (CMB...
Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.
IEEE transactions on neural networks and learning systems
May 2, 2025
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...
Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.
JMIR aging
Apr 30, 2025
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...
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