AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cognitive Dysfunction

Showing 271 to 280 of 501 articles

Clear Filters

A combination of 3-D discrete wavelet transform and 3-D local binary pattern for classification of mild cognitive impairment.

BMC medical informatics and decision making
BACKGROUND: The detection of Alzheimer's Disease (AD) in its formative stages, especially in Mild Cognitive Impairments (MCI), has the potential of helping the clinicians in understanding the condition. The literature review shows that the classifica...

Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge.

The feature extraction of resting-state EEG signal from amnestic mild cognitive impairment with type 2 diabetes mellitus based on feature-fusion multispectral image method.

Neural networks : the official journal of the International Neural Network Society
Recently, combining feature extraction and classification method of electroencephalogram (EEG) signals has been widely used in identifying mild cognitive impairment. However, it remains unclear which feature of EEG signals is best effective in assess...

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

NeuroImage. Clinical
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether ...

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment.

Journal of visualized experiments : JoVE
Mild cognitive impairment (MCI) is the first sign of dementia among elderly populations and its early detection is crucial in our aging societies. Common MCI tests are time-consuming such that indiscriminate massive screening would not be cost-effect...

A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

NeuroImage
Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can delay its progression, no effective cures are available for AD. Accura...

Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.

Psychiatry research
Preserving cognition and mental capacity is critical to aging with autonomy. Early detection of pathological cognitive decline facilitates the greatest impact of restorative or preventative treatments. Artificial Intelligence (AI) in healthcare is th...

Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.

European journal of nuclear medicine and molecular imaging
PURPOSE: Although functional brain imaging has been used for the early and objective assessment of cognitive dysfunction, there is a lack of generalized image-based biomarker which can evaluate individual's cognitive dysfunction in various disorders....