AIMC Topic: Cognitive Dysfunction
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Linguistic cues for automatic assessment of Alzheimer's disease across languages.
Journal of Alzheimer's disease : JAD
Feb 25, 2025
BackgroundMost common forms of dementia, including Alzheimer's disease, are associated with alterations in spoken language.ObjectiveThis study explores the potential of a speech-based machine learning (ML) approach in estimating cognitive impairment,...
SERPINA3: A Novel Therapeutic Target for Diabetes-Related Cognitive Impairment Identified Through Integrated Machine Learning and Molecular Docking Analysis.
International journal of molecular sciences
Feb 24, 2025
Diabetes-related cognitive impairment (DCI) is a severe complication of type 2 diabetes mellitus (T2DM), with limited understanding of its molecular mechanisms hindering effective therapeutic development. This study identified SERPINA3 as a potential...
Cognitive performance classification of older patients using machine learning and electronic medical records.
Scientific reports
Feb 24, 2025
Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improvin...
Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline.
Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
While numerous studies strive to exploit the complementary potential of MRI and PET using learning-based methods, the effective fusion of the two modalities remains a tricky problem due to their inherently distinctive properties. In addition, current...
Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning.
Alzheimer's research & therapy
Feb 13, 2025
BACKGROUND: Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-as...
Machine learning for the early prediction of long-term cognitive outcome in autoimmune encephalitis.
Journal of psychosomatic research
Feb 11, 2025
BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is an immune-mediated disease. Some patients experience persistent cognitive deficits despite receiving immunotherapy. We aimed to develop a prediction model for long-term cognitive outcomes in p...
Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage.
The journal of prevention of Alzheimer's disease
Feb 6, 2025
BACKGROUND: Mild cognitive impairment (MCI) and preclinical MCI (e.g., subjective cognitive decline, SCD) are considered risk states of dementia, such as Alzheimer's Disease (AD). However, it is challenging to accurately predict conversion from norma...
Joint ensemble learning-based risk prediction of Alzheimer's disease among mild cognitive impairment patients.
The journal of prevention of Alzheimer's disease
Feb 5, 2025
OBJECTIVE: Due to the recognition for the importance of early intervention in Alzheimer's disease (AD), it is important to focus on prevention and treatment strategies for mild cognitive impairment (MCI). This study aimed to establish a risk predicti...
Machine learning-based risk prediction of mild cognitive impairment in patients with chronic heart failure: A model development and validation study.
Geriatric nursing (New York, N.Y.)
Feb 1, 2025
Accurate identification of individuals at high risk for mild cognitive impairment (MCI) among chronic heart failure (CHF) patients is crucial for reducing rehospitalization and mortality rates. This study aimed to develop and validate a machine learn...
Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jan 30, 2025
INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict ...
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