AIMC Topic: Alzheimer Disease
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Adaptive template generation for amyloid PET using a deep learning approach.
Human brain mapping
May 11, 2018
Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. In this st...
Identification of Alzheimer's disease and mild cognitive impairment using multimodal sparse hierarchical extreme learning machine.
Human brain mapping
May 7, 2018
Different modalities such as structural MRI, FDG-PET, and CSF have complementary information, which is likely to be very useful for diagnosis of AD and MCI. Therefore, it is possible to develop a more effective and accurate AD/MCI automatic diagnosis...
Localized instance fusion of MRI data of Alzheimer's disease for classification based on instance transfer ensemble learning.
Biomedical engineering online
May 2, 2018
BACKGROUND: Diagnosis of Alzheimer's disease (AD) is very important, and MRI is an effective imaging mode of Alzheimer's disease. There are many existing studies on the diagnosis of Alzheimer's disease based on MRI data. However, there are no studies...
Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model.
IEEE transactions on bio-medical engineering
Apr 9, 2018
Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i.e., regional volumetric measures) and the genetic variants [i.e., single nucleotide polymorphism (SN...
Characteristics of Mild Cognitive Impairment Using the Thai Version of the Consortium to Establish a Registry for Alzheimer's Disease Tests: A Multivariate and Machine Learning Study.
Dementia and geriatric cognitive disorders
Apr 4, 2018
BACKGROUND: The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) developed a neuropsychological battery (CERAD-NP) to screen patients with Alzheimer's dementia. Mild cognitive impairment (MCI) has received attention as a pre-dementi...
Neuropsychological Tests
Cross-Sectional Studies
Female
Cognitive Dysfunction
Translations
Humans
Male
Reproducibility of Results
Socioeconomic Factors
Middle Aged
Aged
Neural Networks, Computer
Support Vector Machine
Mental Recall
Thailand
Aged, 80 and over
Machine Learning
Alzheimer Disease
Verbal Behavior
Classification of Alzheimer's Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling.
Journal of medical systems
Mar 26, 2018
Alzheimer's disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 AD patients and 98 healthy controls was collected using...
Random support vector machine cluster analysis of resting-state fMRI in Alzheimer's disease.
PloS one
Mar 23, 2018
Early diagnosis is critical for individuals with Alzheimer's disease (AD) in clinical practice because its progress is irreversible. In the existing literature, support vector machine (SVM) has always been applied to distinguish between AD and health...
An ensemble learning system for a 4-way classification of Alzheimer's disease and mild cognitive impairment.
Journal of neuroscience methods
Mar 22, 2018
Discriminating Alzheimer's disease (AD) from its prodromal form, mild cognitive impairment (MCI), is a significant clinical problem that may facilitate early diagnosis and intervention, in which a more challenging issue is to classify MCI subtypes, i...
Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.
Scientific reports
Mar 15, 2018
Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite presenting with symptomatic overlap. Currently, there is a need of inexpensive DLB biomarkers which can be fulfilled by electroencephalography (EEG)....
Machine Learning-based Individual Assessment of Cortical Atrophy Pattern in Alzheimer's Disease Spectrum: Development of the Classifier and Longitudinal Evaluation.
Scientific reports
Mar 7, 2018
To develop a new method for measuring Alzheimer's disease (AD)-specific similarity of cortical atrophy patterns at the individual-level, we employed an individual-level machine learning algorithm. A total of 869 cognitively normal (CN) individuals an...
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