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Longitudinal Data Analysis and Time Series Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
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- ADAMS modeling (1)
- Alzheimer disease (1)
- Atrophy (1)
- Gait (1)
- Magnetic resonance imaging (1)
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- Mild cognitive impairment (1)
- Nondestructive testing (1)
- Numerical simulation (1)
- Pattern recognition (1)
- Probability (1)
- Resting state function magnetic resonance imaging (1)
- Social Media (1)
- Spatio-temporal Data Analysis (1)
- Support vector machine (SVM) (1)
- Threat Detection (1)
- Visual Analytics (1)
- Publication
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Articles 1 - 3 of 3
Full-Text Articles in Longitudinal Data Analysis and Time Series
Development Of Anatomical And Functional Magnetic Resonance Imaging Measures Of Alzheimer Disease, Samaneh Kazemifar
Development Of Anatomical And Functional Magnetic Resonance Imaging Measures Of Alzheimer Disease, Samaneh Kazemifar
Electronic Thesis and Dissertation Repository
Alzheimer disease is considered to be a progressive neurodegenerative condition, clinically characterized by cognitive dysfunction and memory impairments. Incorporating imaging biomarkers in the early diagnosis and monitoring of disease progression is increasingly important in the evaluation of novel treatments. The purpose of the work in this thesis was to develop and evaluate novel structural and functional biomarkers of disease to improve Alzheimer disease diagnosis and treatment monitoring. Our overarching hypothesis is that magnetic resonance imaging methods that sensitively measure brain structure and functional impairment have the potential to identify people with Alzheimer’s disease prior to the onset of cognitive decline. …
Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu
Nondestructive Testing And Structural Health Monitoring Based On Adams And Svm Techniques, Gang Jiang, Yi Ming Deng, Ji Tai Niu
The 8th International Conference on Physical and Numerical Simulation of Materials Processing
No abstract provided.
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae
The Summer Undergraduate Research Fellowship (SURF) Symposium
Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …