AI Medical Compendium Topic:
Alzheimer Disease

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Impaired neurogenesis of the dentate gyrus is associated with pattern separation deficits: A computational study.

Journal of integrative neuroscience
The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the ...

Independent Component Analysis-Support Vector Machine-Based Computer-Aided Diagnosis System for Alzheimer's with Visual Support.

International journal of neural systems
Computer-aided diagnosis (CAD) systems constitute a powerful tool for early diagnosis of Alzheimer's disease (AD), but limitations on interpretability and performance exist. In this work, a fully automatic CAD system based on supervised learning meth...

Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

Neurobiology of aging
Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies,...

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

Journal of biomedical semantics
BACKGROUND: Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framewo...

Classification of patients with MCI and AD from healthy controls using directed graph measures of resting-state fMRI.

Behavioural brain research
Brain network alterations in patients with Alzheimer's disease (AD) has been the subject of much investigation, but the biological mechanisms underlying these alterations remain poorly understood. Here, we aim to identify the changes in brain network...

Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
The problem of constructing classifiers from multiple annotators who provide inconsistent training labels is important and occurs in many application domains. Many existing methods focus on the understanding and learning of the crowd behaviors. Sever...

Effectiveness of a social robot, "Paro," in a VA long-term care setting.

Psychological services
Interest in animal assisted interventions (AAI) has grown over the years, but acceptance of AAI by the clinical and research community has been hampered by safety, hygiene, and logistical concerns. Advances in the field of social robotics have provid...

Classification of amyloid status using machine learning with histograms of oriented 3D gradients.

NeuroImage. Clinical
Brain amyloid burden may be quantitatively assessed from positron emission tomography imaging using standardised uptake value ratios. Using these ratios as an adjunct to visual image assessment has been shown to improve inter-reader reliability, howe...

Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia.

International journal of neural systems
A novel technique of quantitative EEG for differentiating patients with early-stage Creutzfeldt-Jakob disease (CJD) from other forms of rapidly progressive dementia (RPD) is proposed. The discrimination is based on the extraction of suitable features...