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Predicting The Progression Of Diabetes Mellitus Using Dynamic Plantar Pressure Parameters, Mathew Sunil Varre
Predicting The Progression Of Diabetes Mellitus Using Dynamic Plantar Pressure Parameters, Mathew Sunil Varre
UNLV Theses, Dissertations, Professional Papers, and Capstones
Introduction: Diabetic peripheral neuropathy is one of the common complications of type-2 diabetes mellitus (DM). Changes in the intrinsic plantar tissue coupled with repetitive mechanical loads and loss of sensation may lead to foot related complications (skin break down, ulcerations, and amputations) in persons with neuropathy if left untreated. The purpose of this dissertation was to stratify individuals with pre-diabetes, diabetes with and without neuropathy using dynamic plantar pressure parameters during walking, using machine learning algorithms.Methods: Plantar pressure data was collected from one hundred participants during walking with pressure measuring insoles fixed between the feet and thin socks. Simultaneously high-definition …
Radiomic Features To Predict Overall Survival Time For Patients With Glioblastoma Brain Tumors Based On Machine Learning And Deep Learning Methods, Lina Chato
UNLV Theses, Dissertations, Professional Papers, and Capstones
Machine Learning (ML) methods including Deep Learning (DL) Methods have been employed in the medical field to improve diagnosis process and patient’s prognosis outcomes. Glioblastoma multiforme is an extremely aggressive Glioma brain tumor that has a poor survival rate. Understanding the behavior of the Glioblastoma brain tumor is still uncertain and some factors are still unrecognized. In fact, the tumor behavior is important to decide a proper treatment plan and to improve a patient’s health. The aim of this dissertation is to develop a Computer-Aided-Diagnosis system (CADiag) based on ML/DL methods to automatically estimate the Overall Survival Time (OST) for …