AI Medical Compendium Journal:
American journal of Alzheimer's disease and other dementias

Showing 1 to 10 of 10 articles

Predicting and Evaluating Cognitive Status in Aging Populations Using Decision Tree Models.

American journal of Alzheimer's disease and other dementias
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...

Alzheimer's Disease Dementia Prevalence in the United States: A County-Level Spatial Machine Learning Analysis.

American journal of Alzheimer's disease and other dementias
A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer's disease (AD) dementia, yet the spatial variability and relative importance of the most influential factors remain underexplored. We compiled various w...

Automatic Detection of Cognitive Impairment in Patients With White Matter Hyperintensity Using Deep Learning and Radiomics.

American journal of Alzheimer's disease and other dementias
White matter hyperintensity (WMH) is associated with cognitive impairment. In this study, 79 patients with WMH from hospital 1 were randomly divided into a training set (62 patients) and an internal validation set (17 patients). In addition, 29 WMH p...

New-Onset Alzheimer's Disease and Normal Subjects 100% Differentiated by P300.

American journal of Alzheimer's disease and other dementias
Previous work has suggested that evoked potential analysis might allow the detection of subjects with new-onset Alzheimer's disease, which would be useful clinically and personally. Here, it is described how subjects with new-onset Alzheimer's diseas...

Computer-Aided Diagnosis System for Alzheimer's Disease Using Different Discrete Transform Techniques.

American journal of Alzheimer's disease and other dementias
The different discrete transform techniques such as discrete cosine transform (DCT), discrete sine transform (DST), discrete wavelet transform (DWT), and mel-scale frequency cepstral coefficients (MFCCs) are powerful feature extraction techniques. Th...

Heart Rate and its Variability From Short-Term ECG Recordings as Potential Biomarkers for Detecting Mild Cognitive Impairment.

American journal of Alzheimer's disease and other dementias
Alterations in Heart Rate (HR) and Heart Rate Variability (HRV) reflect autonomic dysfunction associated with neurodegeneration making them biomarkers suitable for detecting Mild Cognitive Impairment (MCI). The study involves 297 urban Indian parti...

A Study on Machine Learning Models in Detecting Cognitive Impairments in Alzheimer's Patients Using Cerebrospinal Fluid Biomarkers.

American journal of Alzheimer's disease and other dementias
Several research studies have demonstrated the potential use of cerebrospinal fluid biomarkers such as amyloid beta 1-42, T-tau, and P-tau, in early diagnosis of Alzheimer's disease stages. The levels of these biomarkers in conjunction with the demen...

Identification of Dementia & Mild Cognitive Impairment in Chinese Elderly Using Machine Learning.

American journal of Alzheimer's disease and other dementias
OBJECTIVE: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment.

Usability and Acceptability of Social Robot Pets Among Community-Dwelling Veterans Living With Dementia and Their Caregivers.

American journal of Alzheimer's disease and other dementias
Social robot pets promote engagement and psychosocial well-being among older adults, yet little is known about their use among community-dwelling Veterans living with dementia. This programmatic evaluation used a within subjects, pre-post design to e...

Machine-Learning Algorithms Based on Screening Tests for Mild Cognitive Impairment.

American journal of Alzheimer's disease and other dementias
BACKGROUND: The mobile screening test system for mild cognitive impairment (mSTS-MCI) was developed and validated to address the low sensitivity and specificity of the Montreal Cognitive Assessment (MoCA) widely used clinically.