AIMC Topic: Mental Status and Dementia Tests
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Dementia Overdiagnosis in Younger, Higher Educated Individuals Based on MMSE Alone: Analysis Using Deep Learning Technology.
Journal of Korean medical science
Mar 10, 2025
BACKGROUND: Dementia is a multifaceted disorder that affects cognitive function, necessitating accurate diagnosis for effective management and treatment. Although the Mini-Mental State Examination (MMSE) is widely used to assess cognitive impairment,...
Machine Learning-Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study.
Neurology India
Dec 17, 2024
BACKGROUND AND OBJECTIVE: Early identification of post-stroke cognitive impairment (PSCI) is an important challenge for clinicians. In this study, we aimed to build a machine learning-based prediction model for PSCI and uncover potential risk factors...
Establishing a machine learning dementia progression prediction model with multiple integrated data.
BMC medical research methodology
Nov 22, 2024
OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical tools for predicting the progression of degenerative dementia are highly valuable. Machine learning (ML) methods facilitate the construction of effec...
Intelligent prediction of Alzheimer's disease via improved multifeature squeeze-and-excitation-dilated residual network.
Scientific reports
May 25, 2024
This study aimed to address the issue of larger prediction errors existing in intelligent predictive tasks related to Alzheimer's disease (AD). A cohort of 487 enrolled participants was categorized into three groups: normal control (138 individuals),...
Assess the documentation of cognitive tests and biomarkers in electronic health records via natural language processing for Alzheimer's disease and related dementias.
International journal of medical informatics
Dec 21, 2022
BACKGROUND: Cognitive tests and biomarkers are the key information to assess the severity and track the progression of Alzheimer's' disease (AD) and AD-related dementias (AD/ADRD), yet, both are often only documented in clinical narratives of patient...
A combination of support vector machine and voxel-based morphometry in adult male alcohol use disorder patients with cognitive deficits.
Brain research
Aug 31, 2021
Cognitive performance deteriorates with drinking. However, the neural basis of cognitive deficits in alcohol use disorder (AUD) is still incompletely understood. Here we examined the relationship between overall drinking, brain structural alterations...
Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.
Neuroscience letters
Jun 24, 2021
The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine learning algorithms to examine patterns of stress-immune networks with cognitive impairment in chronic ...
Diagnosis of Alzheimer's Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN).
Computational and mathematical methods in medicine
Apr 27, 2021
The automatic diagnosis of Alzheimer's disease plays an important role in human health, especially in its early stage. Because it is a neurodegenerative condition, Alzheimer's disease seems to have a long incubation period. Therefore, it is essential...
Brain
Severity of Illness Index
Deep Learning
Functional Neuroimaging
Computational Biology
Humans
Neural Networks, Computer
Algorithms
Databases, Factual
Support Vector Machine
Alzheimer Disease
Magnetic Resonance Imaging
Image Interpretation, Computer-Assisted
Decision Trees
Early Diagnosis
Discriminant Analysis
Mental Status and Dementia Tests
Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.
JAMA network open
Feb 1, 2021
IMPORTANCE: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.
Deep learning prediction of falls among nursing home residents with Alzheimer's disease.
Geriatrics & gerontology international
Apr 8, 2020
AIM: This study aimed to use a convolutional neural network (CNN) to investigate the associations between the time of falling and multiple complicating factors, including age, dementia severity, lower extremity strength and physical function, among n...
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