Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 9 of 9 for “"Alzheimer’s disease neuroimaging initiative"”.
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Neural Network Classification of Hippocampal Regions Based on Neuroimaging Studies of Alzheimer's Disease
… been prepared for the management of the ADNI (Alzheimer’s Disease Neuroimaging Initiative) data. This script contains the segmentation of brain images to extract the hippocampal region using the FreeSurfer tool. Secondly, a series of tests have been conducted to find the optimal parameters …
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The Relationship Between Neuropsychological Functioning, Biomarker AV-1451, and Subjective Memory Impairment in a Cognitively Normal Sample
… impairment (MCI) is often a prodromal stage for Alzheimer’s disease (AD) development, with those diagnosed with MCI at increased risk for developing AD. The present study aimed to provide data to support a prodromal stage of MCI via analysis utilizing the neuropsychological domain of memory, …
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Hippocampal Volume and the Detection of Mild Cognitive Impairment in an Older Adult Population: Assessing Performance on Cognitive Screeners Administered In-Person and Electronically
… 445 older adult participants selected from the Alzheimer’s Disease Neuroimaging Initiative 3. Participants met criteria for diagnostic classifications of cognitively normal and mild cognitive impairment and had undergone neuropsychological testing consisting of the Montreal Cognitive Assessment …
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Biomarker-And Pathway-Informed Polygenic Risk Scores for Alzheimer's Disease and Related Disorders
… individual’s genetic susceptibility in complex diseases like Alzheimer’s disease (AD) is challenging as multiple variants each contribute a small portion of the overall risk. Polygenic Risk Scores (PRS) are a mathematical construct or composite that aggregates the small effects of multiple …
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Linear mixed model for multi-level omics data
Accurate disease prediction is expected to facilitate the precision medicine with emerging genetic findings and other demonstrated knowledge (Ashley, 2015). While rare genetic variants, multi-omic information and family structure have provided unprecedented data resources for predictive studies, …
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Bayesian Tensor Modeling of High-Dimensional Neuroimaging Data
Neuroimaging has played a pivotal role in advancing the understanding of neurological and psychiatric conditions by providing comprehensive insights into structural and functional brain changes. Techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), and diffusion …
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Novel Network-Based Models for High-dimensional Data
… emphasizing its potential to unravel com plex disease mechanisms and enhance clinical predictions in oncology. We further demonstrated the versatility of our method by applying it to Alzheimer’s disease (AD) research. Using Fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging and …
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A Machine Learning Classification Framework for Early Prediction of Alzheimer’s Disease
… the highest costs in health and social care is Alzheimer’s disease, which gradually kills neurons and causes patients to lose loving memories, the ability to recognise family members, childhood memories, and even the ability to follow simple instructions. Alzheimer’s disease is irreversible, …
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Evaluation of Cerebral Lateral Ventricular Enlargement Derived from Magnetic Resonance Imaging: A Candidate Biomarker of Alzheimer Disease Progression in Vivo
Alzheimer disease (AD) is the most common form of dementia and has grievous mortality rates. Measuring brain volumes from structural magnetic resonance images (MRI) may be useful for illuminating disease progression. The goal of this thesis was to (1) help refine a novel technique used to segment …