AIMC Topic: Cognitive Dysfunction
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Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.
Scientific reports
Aug 10, 2025
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...
Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.
Alzheimer's research & therapy
Aug 7, 2025
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...
Alzheimer's disease risk prediction using machine learning for survival analysis with a comorbidity-based approach.
Scientific reports
Aug 6, 2025
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi...
Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review.
JMIR mental health
Aug 5, 2025
BACKGROUND: Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GISs) ...
TA-SSM net: tri-directional attention and structured state-space model for enhanced MRI-Based diagnosis of Alzheimer's disease and mild cognitive impairment.
BMC medical imaging
Jul 31, 2025
Early diagnosis of Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI), is critical for effective prevention and treatment. Computer-aided diagnosis using magnetic resonance imaging (MRI) provides a cost-effective and objectiv...
Prediction of postoperative visual cognitive impairment using graph theory and machine learning based on resting-state brain networks.
BMC medical imaging
Jul 30, 2025
BACKGROUND: Visual cognitive impairment is among the most common postoperative cognitive dysfunctions, significantly impacting recovery and quality of life in elderly patients. However, effective preoperative prediction methods remain lacking. We dev...
A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study.
Scientific reports
Jul 24, 2025
This study aims to identify depressive risks in elderly individuals with subjective cognitive decline (SCD) and develop a predictive model using machine learning algorithms to enable timely interventions.Data from the 2015 and 2018 waves of the China...
Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device.
Scientific reports
Jul 20, 2025
Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but trad...
Developing an explainable machine learning and fog computing-based visual rating scale for the prediction of dementia progression.
Scientific reports
Jul 16, 2025
Recently, dementia research has primarily concentrated on using Magnetic Resonance Imaging (MRI) to develop learning models in processing and analyzing brain data. However, these models often cannot provide early detection of affected brain regions. ...
Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.
Scientific reports
Jul 15, 2025
Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This c...
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