Biomedical Commons^™

Design Of An Affordable Rotating Drum Electrospinner For Classroom Education, Peder Solberg

The Journal of Undergraduate Research

Electrospinning is a technology used to generate small fibers down to nano-scale size. This method of fiber creation has been around for many years. However, in recent years electrospinning has found increased applications, especially in the area of tissue engineering due to its ability to create fibers with properties similar to the extracellular matrix in tissue. An electrospinning platform can illustrate concepts of engineering, electro-mechanical system design, manufacturing, and biomedical applications in one single package. Hence, it provides an excellent opportunity to integrate into secondary (middle and high school) and post-secondary (undergraduate) technology education.

Furthermore, just as integration of 3D …

Chronic Risk And Disease Management Model Using Structured Query Language And Predictive Analysis, Mamata Ojha

Electronic Theses and Dissertations

Individuals with chronic conditions are the ones who use health care most frequently and more than 50% of top ten causes of death are chronic diseases in United States and these members always have health high risk scores. In the field of population health management, identifying high risk members is very important in terms of patient health care, disease management and cost management. Disease management program is very effective way of monitoring and preventing chronic disease and health related complications and risk management allows physicians and healthcare companies to reduce patient’s health risk, help identifying members for care/disease management along …

Adaptive Interventions Treatment Modelling And Regimen Optimization Using Sequential Multiple Assignment Randomized Trials (Smart) And Q-Learning, Abiral Baniya

Electronic Theses and Dissertations

Nowadays, pharmacological practices are focused on a single best treatment to treat a disease which sounds impractical as the same treatment may not work the same way for every patient. Thus, there is a need of shift towards more patient-centric rather than disease-centric approach, in which personal characteristics of a patient or biomarkers are used to determine the tailored optimal treatment. The “one size fits all” concept is contradicted by research area of personalized medicine. The Sequential Multiple Assignment Randomized Trial (SMART) is a multi-stage trials to inform the development of dynamic treatment regimens (DTR’s). In SMART, a subject is …

A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun

Electronic Theses and Dissertations

The medical industry is currently working on a fully autonomous surgical system, which is considered a novel modality to go beyond technical limitations of conventional surgery. In order to apply an autonomous surgical system to knees, one of the primarily responsible areas for supporting the total weight of human body, accurate segmentation of bones from knee Magnetic Resonance Imaging (MRI) scans plays a crucial role. In this paper, we propose employing the Scale Space Local Binary Pattern (SSLBP) feature extraction, a variant of local binary pattern extractions, for detecting bones from knee images. The proposed methods consist of two phases. …

Enhanced Breast Cancer Classification With Automatic Thresholding Using Support Vector Machine And Harris Corner Detection, Mohammad Taheri

Electronic Theses and Dissertations

Image classification and extracting the characteristics of a tumor are the powerful tools in medical science. In case of breast cancer medical treatment, the breast cancer classification methods can be used to classify input images as benign and malignant classes for better diagnoses and earlier detection with breast tumors. However, classification process can be challenging because of the existence of noise in the images, and complicated structures of the image. Manual classification of the images is timeconsuming, and need to be done only by medical experts. Hence using an automated medical image classification tool is useful and necessary. In addition, …

Sickle Blood Cell Detection Based On Image Segmentation, Kholoud Alotaibi

Electronic Theses and Dissertations

Red blood cells have a vital role in human health. Red blood cells have a circular shape and a concave surface and exchange the gasses between the inside and outside of the body. However, at times, these normally round cells become sickle shaped, which is an indication of sickle cell disease. This paper introduces a unique approach to detect sickle blood cells in blood samples using image segmentation and shape detection. This method is based on calculating the max axis and min axis of the cell. The form factor is computed using these properties to determine whether the cell is …

Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo

Electronic Theses and Dissertations

Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The main purpose of breast cancer classification is to classify abnormalities into benign or malignant classes and thus help physicians with further analysis by minimizing potential errors that can be made by fatigued or inexperienced physicians. This paper proposes a new shape metric based on the area ratio of a circle to classify mammographic images into benign and malignant class. Support Vector Machine is used as a machine learning tool for training and classification purposes. The improved …