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Biomedical Engineering and Bioengineering Commons™
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- Aging (1)
- Alzheimer's disease (1)
- Alzheimer’s disease (1)
- Amplitude of low fluctuation(alff) (1)
- Autoencoders (1)
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- CSF expansion (1)
- Cerebrospinal fluid expansion (1)
- Cognition (1)
- Computer-aided diagnosis (1)
- Data Reduction (1)
- Deep Learning (1)
- Dimensionality reduction (1)
- Edge Computing (1)
- Functional connectivity (1)
- Grey matter loss (1)
- Hippocampal volume loss (1)
- Human Activity Recognition (1)
- IoT (1)
- Longitudinal analysis (1)
- Mild cognitive impairment (MCI) (1)
- Multiclass classification (1)
- Multimodal analysis (1)
- Natural language processing (NLP) (1)
- Regional homogenitygenty (reho) (1)
- Resting state functional magnetic resonance imaging (rs-fmri) (1)
- Structural brain changes (1)
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Articles 1 - 4 of 4
Full-Text Articles in Biomedical Engineering and Bioengineering
Comparison Of Longitudinal Changes In Resting State Functional Magnetic Resonance Imaging Between Alzheimer’S And Healthy Controls, Berk Can Yilmaz
Comparison Of Longitudinal Changes In Resting State Functional Magnetic Resonance Imaging Between Alzheimer’S And Healthy Controls, Berk Can Yilmaz
Theses
Resting State Functional Magnetic Resonance Imaging (rs-fMRI) is a technique that is widely used for analyzing brain function using different approaches and methods. This study involves rs-fMRI analysis of Blood Oxygenation Level Dependent (BOLD) signals acquired from Alzheimer’s disease (AD) Patients and Healthy Controls (HC). Each subject in the study had both functional and anatomical images with at least one rs-fMRI scan with their Anatomical (T1) scans. Previous rs-fMRI studies have demonstrated that AD shows differences in Amplitude of Low Frequency (<0.1 Hz) Fluctuations (ALFF), and Regional Homogeneity (ReHo) measures according to HCs.
The aim of the study is to investigate individual and group level differences using ReHo and mALFF related …
0.1>Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh
Electronic Thesis and Dissertation Repository
Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons, Charles D. Smith, Linda J. Van Eldik, Gregory A. Jicha, Frederick A. Schmitt, Peter T. Nelson, Erin L. Abner, Richard J. Kryscio, Richard R. Murphy, Anders H. Andersen
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons, Charles D. Smith, Linda J. Van Eldik, Gregory A. Jicha, Frederick A. Schmitt, Peter T. Nelson, Erin L. Abner, Richard J. Kryscio, Richard R. Murphy, Anders H. Andersen
Neurology Faculty Publications
Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70-78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a …
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …