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Cognitive Dysfunction

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The Attitudes and Perceptions of Older Adults With Mild Cognitive Impairment Toward an Assistive Robot.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
The purpose of this study was to explore perceived difficulties and needs of older adults with mild cognitive impairment (MCI) and their attitudes toward an assistive robot to develop appropriate robot functionalities. Twenty subjects were recruited ...

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Brain structure & function
Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous methods that considered simple low-level features such as gray matter tis...

MRI-based diagnostic model for Alzheimer's disease using 3D-ResNet.

Biomedical physics & engineering express
Alzheimer's disease (AD), a progressive neurodegenerative disorder, is the leading cause of dementia worldwide and remains incurable once it begins. Therefore, early and accurate diagnosis is essential for effective intervention. Leveraging recent ad...

An Explainable-AI Based Approach Towards Measuring Cognitive Reserve.

Studies in health technology and informatics
Cognitive Reserve (CR) refers to the brain's ability to compensate for brain damage or age-related changes, which can explain why some individuals show greater cognitive resilience to brain pathology despite damage or age-related changes. Understandi...

WMH-DualTasker: A Weakly Supervised Deep Learning Model for Automated White Matter Hyperintensities Segmentation and Visual Rating Prediction.

Human brain mapping
White matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. WMH severity is typically assessed via visual rating scales and through volumetric segmentation. While visual rating scales are commonly use...

Examination of the relationship between D-amino acid profiles and cognitive function in individuals with mild cognitive impairment: a machine learning approach.

The international journal of neuropsychopharmacology
BACKGROUND: The global prevalence of dementia is significantly increasing. Early detection and prevention strategies, particularly for mild cognitive impairment (MCI), are crucial but currently hindered by the lack of established biomarkers. Here, we...

Dynamic and Static Structure-Function Coupling With Machine Learning for the Early Detection of Alzheimer's Disease.

Human brain mapping
The progression of Alzheimer's disease (AD) involves complex changes in brain structure and function that are driven by their interaction, making structure-function coupling (SFC) a valuable indicator for early detection of AD. Static SFC refers to t...

Evaluating Traditional, Deep Learning and Subfield Methods for Automatically Segmenting the Hippocampus From MRI.

Human brain mapping
Given the relationship between hippocampal atrophy and cognitive impairment in various pathological conditions, hippocampus segmentation from MRI is an important task in neuroimaging. Manual segmentation, though considered the gold standard, is time-...

Using machine learning models to identify severe subjective cognitive decline and related factors in nurses during the menopause transition: a pilot study.

Menopause (New York, N.Y.)
OBJECTIVE: This study aims to develop and validate a machine learning model for identifying individuals within the nursing population experiencing severe subjective cognitive decline (SCD) during the menopause transition, along with their associated ...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.