AI Medical Compendium Topic:
Alzheimer Disease

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Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer's disease.

BMC medical informatics and decision making
BACKGROUND: Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful relationships between entities au...

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.

Genomics, proteomics & bioinformatics
Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by ...

Discriminative margin-sensitive autoencoder for collective multi-view disease analysis.

Neural networks : the official journal of the International Neural Network Society
Medical prediction is always collectively determined based on bioimages collected from different sources or various clinical characterizations described from multiple physiological features. Notably, learning intrinsic structures from multiple hetero...

Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review.

Computer methods and programs in biomedicine
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries. From a research point of view, impressive results have been reported using computer-aided algorithms, but clinically no practical diagnostic method is available. I...

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....

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data.

BMC medical informatics and decision making
BACKGROUND: Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settin...

Brain pathology identification using computer aided diagnostic tool: A systematic review.

Computer methods and programs in biomedicine
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-of-life by reducing human errors in diagnosis. CAD can expedite decision-making on complex clinical data automatically. Since brain diseases can be fatal, rapi...

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

NeuroImage
Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lack of sufficient longitudinal data required for the development of novel machine learning algorithms. This study proposes a novel machine learning algo...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

Computers in biology and medicine
BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this arti...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

Journal of neural engineering
OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due t...