AIMC Topic: Alzheimer Disease
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Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.
Computers in biology and medicine
Oct 31, 2019
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
Oct 29, 2019
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...
Using path signatures to predict a diagnosis of Alzheimer's disease.
PloS one
Sep 19, 2019
The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input p...
Quantifying brain metabolism from FDG-PET images into a probability of Alzheimer's dementia score.
Human brain mapping
Sep 10, 2019
F-fluorodeoxyglucose positron emission tomography (FDG-PET) enables in-vivo capture of the topographic metabolism patterns in the brain. These images have shown great promise in revealing the altered metabolism patterns in Alzheimer's disease (AD). ...
Predicting Drug-Disease Associations via Using Gaussian Interaction Profile and Kernel-Based Autoencoder.
BioMed research international
Aug 27, 2019
Computational drug repositioning, designed to identify new indications for existing drugs, significantly reduced the cost and time involved in drug development. Prediction of drug-disease associations is promising for drug repositioning. Recent years...
Toward an interpretable Alzheimer's disease diagnostic model with regional abnormality representation via deep learning.
NeuroImage
Aug 22, 2019
In this paper, we propose a novel method for magnetic resonance imaging based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis that systematically integrates voxel-based, region-based, and patch-based approaches into a unified fr...
Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.
Artificial intelligence in medicine
Aug 9, 2019
INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learnin...
Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.
International journal of medical informatics
Aug 6, 2019
INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly represent risk factors for dementia in general or dementia due to Alzheimer's disease (AD). These lifestyle exposures are mainly mentioned in free-text ...
Trends in Alzheimer's Disease Research Based upon Machine Learning Analysis of PubMed Abstracts.
International journal of biological sciences
Aug 6, 2019
About 29.8 million people worldwide had been diagnosed with Alzheimer's disease (AD) in 2015, and the number is projected to triple by 2050. In 2018, AD was the fifth leading cause of death in Americans with 65 years of age or older, but the progress...
Characterizing Alzheimer's Disease With Image and Genetic Biomarkers Using Supervised Topic Models.
IEEE journal of biomedical and health informatics
Jul 31, 2019
Neuroimaging and genetic biomarkers have been widely studied from discriminative perspectives towards Alzheimer's disease (AD) classification, since neuroanatomical patterns and genetic variants are jointly critical indicators for AD diagnosis. Gener...
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