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Full-Text Articles in Medicine and Health Sciences
An Explainable Deep Learning Prediction Model For Severity Of Alzheimer's Disease From Brain Images, Godwin O. Ekuma
An Explainable Deep Learning Prediction Model For Severity Of Alzheimer's Disease From Brain Images, Godwin O. Ekuma
MSU Graduate Theses
Deep Convolutional Neural Networks (CNNs) have become the go-to method for medical imaging classification on various imaging modalities for binary and multiclass problems. Deep CNNs extract spatial features from image data hierarchically, with deeper layers learning more relevant features for the classification application. The effectiveness of deep learning models are hampered by limited data sets, skewed class distributions, and the undesirable "black box" of neural networks, which decreases their understandability and usability in precision medicine applications. This thesis addresses the challenge of building an explainable deep learning model for a clinical application: predicting the severity of Alzheimer's disease (AD). AD …
An Investigative Study Into Alzheimer’S Disease (Ad): Development, Pathway And Progression, And Novel Treatment, Aruha Khan
Chancellor’s Honors Program Projects
No abstract provided.
Alzheimer’S And Patient Caregiver Burnout: A Comprehensive Review Of The Literature, Madeline J. Hekeler
Alzheimer’S And Patient Caregiver Burnout: A Comprehensive Review Of The Literature, Madeline J. Hekeler
Senior Honors Projects, 2020-current
The term ‘silent epidemic’ has become fitting for Alzheimer’s disease, as it is now the sixth leading cause of death in the US. Caring for AD patients at home in the US costs billions of dollars each year. The current comprehensive literature review discusses the background/history of AD, pathology and modes of transmission of AD, behavioral and natural risk factors, prevention and treatment options, and how the aforementioned factors contribute to caregiver burnout and subsequently affect the AD patient. The extensive examination of the literature determined several gaps to be addressed. More specifically, burnout among AD caregivers has become an …
Investigating Diffusion Tensor Imaging Correlates Of Cognitive Impairment In Idiopathic Normal Pressure Hydrocephalus And Alzheimer's Disease, Omar Hasan, Omar Hasan
Investigating Diffusion Tensor Imaging Correlates Of Cognitive Impairment In Idiopathic Normal Pressure Hydrocephalus And Alzheimer's Disease, Omar Hasan, Omar Hasan
Dissertations & Theses (Open Access)
Modest expansion of the human brain cerebrospinal fluid (CSF)-filled ventricles is normal with aging, and because of this, it can be difficult for physicians to accurately diagnose and treat enlarged ventricles (ventriculomegaly), called hydrocephalus1 (fluid or water in the brain) Ventriculomegaly occurs due to an obstruction (such as a blood clot or tumor), or a change in CSF absorption2. Primary hydrocephalus, also called idiopathic normal pressure hydrocephalus (iNPH), is non-obstructive and may be comorbid with other neurodegenerative diseases such as Alzheimer’s disease (AD) or frontotemporal dementia (FTD). Clinically, it can be difficult to tell whether the pathophysiological …
Early Diagnosis Of Alzheimer’S Disease In The Primary Care Setting, Raymond R. Romano
Early Diagnosis Of Alzheimer’S Disease In The Primary Care Setting, Raymond R. Romano
Theses and Dissertations (ETD)
The burden of Alzheimer’s disease (AD) affects not just the individual but also families, providers, and society. Early recognition and diagnosis of AD may reduce cost by reducing interaction with the health care system, earlier initiation of treatment, and prolonging time to long- term care. Primary care providers, the first contact for diagnosis of patients with AD, are not fulfilling the potential of early diagnosis for a variety of reasons. Biomarkers of AD emerge on average 15 to 20 years before clinical diagnosis, yet currently established biomarkers are not easily available in the primary care setting. A growing body of …
Digital Morphometry : A Taxonomy Of Morphological Filters And Feature Parameters With Application To Alzheimer's Disease Research, Andrew Mehnert
Digital Morphometry : A Taxonomy Of Morphological Filters And Feature Parameters With Application To Alzheimer's Disease Research, Andrew Mehnert
Theses: Doctorates and Masters
In this thesis the expression digital morphometry collectively describes all those procedures used to obtain quantitative measurements of objects within a two-dimensional digital image. Quantitative measurement is a two-step process: the application of geometrical transformations to extract the features of interest, and then the actual measurement of these features. With regard to the first step the morphological filters of mathematical morphology provide a wealth of suitable geometric transfomations. Traditional radiometric and spatial enhancement techniques provide an additional source of transformations. The second step is more classical (e.g. Underwood, 1970; Bookstein, 1978; and Weibull, 1980); yet here again mathematical morphology is …