Computer Engineering Commons^™

Machine Learning Approaches For Lung Cancer Diagnosis., Ahmed Mahmoud Ahmed Shaffie

Electronic Theses and Dissertations

The enormity of changes and development in the field of medical imaging technology is hard to fathom, as it does not just represent the technique and process of constructing visual representations of the body from inside for medical analysis and to reveal the internal structure of different organs under the skin, but also it provides a noninvasive way for diagnosis of various disease and suggest an efficient ways to treat them. While data surrounding all of our lives are stored and collected to be ready for analysis by data scientists, medical images are considered a rich source that could provide …

Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies, Fengbo Zheng

Theses and Dissertations--Computer Science

An ontology provides a formalized representation of knowledge within a domain. In biomedicine, ontologies have been widely used in modern biomedical applications to enable semantic interoperability and facilitate data exchange. Given the important roles that biomedical ontologies play, quality issues such as incompleteness, if not addressed, can affect the quality of downstream ontology-driven applications. However, biomedical ontologies often have large sizes and complex structures. Thus, it is infeasible to uncover potential quality issues through manual effort. In this dissertation, we introduce automated and scalable approaches for auditing the completeness of biomedical ontologies. We mainly focus on two incompleteness issues -- …

A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi

Graduate Theses, Dissertations, and Problem Reports

Long non coding Ribonucleic Acids (lncRNAs) can be localized to different cellular components, such as the nucleus, exosome, cytoplasm, ribosome, etc. Their biological functions can be influenced by the region of the cell they are located. Many of these lncRNAs are associated with different challenging diseases. Thus, it is crucial to study their subcellular localization. However, compared to the vast number of lncRNAs, only relatively few have annotations in terms of their subcellular localization. Conventional computational methods use q-mer profiles from lncRNA sequences and then train machine learning models, such as support vector machines and logistic regression with the profiles. …

Imparting 3d Representations To Artificial Intelligence For A Full Assessment Of Pressure Injuries., Sofia Zahia

Electronic Theses and Dissertations

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning …

Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi

General Engineering

Presently, there is an insufficient availability of human experts to assist students in reading competency and comprehension. Our team’s goal was to create an improved socially assistive robot for use by therapists, teachers, and parents to help children and adults develop reading skills while they do not have access to specialists. HAPI is a socially assistive robot that we created with the goal of helping students practice their reading comprehension skills. HAPI enables a student to improve their reading skills without an educator present, while enabling educators to review the student's performance remotely. Design constraints included: physical size, weight, duration …

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …

Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes

Honors Theses

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified into two main …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Increasing Performance Of Classifiers For Ssvep-Based Brain-Computer Interfaces Using Extension Methods, Ethan Douglas Webster

Legacy Theses & Dissertations (2009 - 2024)

Brain-computer interfaces (BCI) provide an alternative communication method that does not require standard physical mediums (speech, typing, etc.). These systems have been implemented to provide additional communication and control options for people with certain motor disabilities. Classification is an important part of BCI systems and consists of inferring user commands from brain activity. Supervised classification methods often achieve higher accuracy, but unsupervised classification methods are useful when training is not practical for the user. This thesis focuses on unsupervised classification algorithms used for a BCI speller application and presents extensions for two existing classifiers that improve classification accuracy and thus …

Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi

Doctoral Dissertations

“Cervical cancer is the fourth most frequent cancer that affects women worldwide. Assessment of cervical intraepithelial neoplasia (CIN) through histopathology remains as the standard for absolute determination of cancer. The examination of tissue samples under a microscope requires considerable time and effort from expert pathologists. There is a need to design an automated tool to assist pathologists for digitized histology slide analysis. Pre-cervical cancer is generally determined by examining the CIN which is the growth of atypical cells from the basement membrane (bottom) to the top of the epithelium. It has four grades, including: Normal, CIN1, CIN2, and CIN3. In …

A Wearable Mechatronic Device For Hand Tremor Monitoring And Suppression: Development And Evaluation, Yue Zhou

Electronic Thesis and Dissertation Repository

Tremor, one of the most disabling symptoms of Parkinson's disease (PD), significantly affects the quality of life of the individuals who suffer from it. These people live with difficulties with fine motor tasks, such as eating and writing, and suffer from social embarrassment. Traditional medicines are often ineffective, and surgery is highly invasive and risky. The emergence of wearable technology facilitates an externally worn mechatronic tremor suppression device as a potential alternative approach for tremor management. However, no device has been developed for the suppression of finger tremor that has been validated on a human.

It has been reported in …

Quantifying The Outcomes Of A Virtual Reality (Vr)-Based Gamified Neck Rehabilitation, Shahan Salim

Electronic Thesis and Dissertation Repository

Neck pain is a major global public health concern and adds a significant financial burden to both the healthcare system as well as people suffering from it. Additionally, it presents measurement and evaluation challenges for clinicians as well as adherence challenges and treatment barriers for the patients. We have developed a virtual reality (VR)-based video game that can be used to capture outcomes that may aid in the assessment and treatment of neck pain. We investigated: (i) performance metrics of overall accuracy, accuracy based on movement difficulty, duration, and total envelope of movement; (ii) stability across sessions; (iii) accuracy across …

Large Scale Electronic Health Record Data And Echocardiography Video Analysis For Mortality Risk Prediction, Alvaro Emilio Ulloa Cerna

Electrical and Computer Engineering ETDs

Electronic health records contain the clinical history of patients. The enormous potential for discovery in such a rich dataset is hampered by their complexity. We hypothesize that machine learning models trained on EHR data can predict future clinical events significantly better than current models. We analyze an EHR database of 594,862 Echocardiography studies from 272,280 unique patients with both unsupervised and supervised machine learning techniques.

In the unsupervised approach, we first develop a simulation framework to evaluate a family of different clustering pipelines. We apply the optimized approach to 41,645 patients with heart failure without providing any survival information to …

Justrun - Social Gps Running Game, Riley Bergin, Maggie Cai, Simran Judge, Grace Ling

Interdisciplinary Design Senior Theses

With advances in technology allowing people to live more sedentary lives, more and more people are struggling to live a healthy active lifestyle. In the efforts to combat unhealthy styles of living, we wish to introduce a mobile app that takes advantage of motivational game mechanics to motivate players will make go on runs regularly.

Stackcbpred: A Stacking Based Prediction Of Protein-Carbohydrate Binding Sites From Sequence, Suraj Gattani

University of New Orleans Theses and Dissertations

Carbohydrate-binding proteins play vital roles in many vital biological processes and study of these interactions, at residue level, are useful in treating many critical diseases. Analyzing the local sequential environments of the binding and non-binding regions to predict the protein-carbohydrate binding sites is one of the challenging problems in molecular and computational biology. Prediction of such binding sites, directly from sequences, using computational methods, can be useful to fast annotate the binding sites and guide the experimental process. Because the number of carbohydrate-binding residues is significantly lower than non-carbohydrate-binding residues, most of the methods developed are biased towards over predicting …

The Affective Perceptual Model: Enhancing Communication Quality For Persons With Pimd, Jadin Tredup

UNLV Theses, Dissertations, Professional Papers, and Capstones

Methods for prolonged compassionate care for persons with Profound Intellectual and Multiple Disabilities (PIMD) require a rotating cast of import people in the subjects life in order to facilitate interaction with the external environment. As subjects continue to age, dependency on these people increases with complexity of communications while the quality of communication decreases. It is theorized that a machine learning (ML) system could replicate the attuning process and replace these people to promote independence. This thesis extends this idea to develop a conceptual and formal model and system prototype.

The main contributions of this thesis are: (1) proposal of …

Machine Learning Solution To Organ-At-Risk Segmentation For Radiation Treatment Planning, Brie Goo, Katrina May, Haobo Zhang, James Olivas

Interdisciplinary Design Senior Theses

In the treatment of cancer using ionizing radiation, it is important to design a treatment plan such that dose to normal, healthy organs is sufficiently low. Today, segmentation requires a trained human to carefully outline, or segment, organs on each slice of a treatment planning computed tomography (CT) scan but it is laborious, time-consuming, and contains intra- and inter-rater variability. Currently, existing clinical automation technology relies on atlas-based automation, which has limited segmentation accuracy. Thus the auto-segmentations require post process editing by an expert. In this paper, we propose a machine learning solution that shortens the segmentation time of organs-at-risk …

Estimation And Prediction Of The Human Gait Dynamics For The Control Of An Ankle-Foot Prosthesis, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable …

Estimation Of Multi-Directional Ankle Impedance As A Function Of Lower Extremity Muscle Activation, Lauren Knop

Dissertations, Master's Theses and Master's Reports

The purpose of this research is to investigate the relationship between the mechanical impedance of the human ankle and the corresponding lower extremity muscle activity. Three experimental studies were performed to measure the ankle impedance about multiple degrees of freedom (DOF), while the ankle was subjected to different loading conditions and different levels of muscle activity. The first study determined the non-loaded ankle impedance in the sagittal, frontal, and transverse anatomical planes while the ankle was suspended above the ground. The subjects actively co-contracted their agonist and antagonistic muscles to various levels, measured using electromyography (EMG). An Artificial Neural Network …

Testing And Validation Framework For Closed-Loop Physiology Management Systems For Critical And Perioperative Care, Farooq M. Gessa

Master’s Theses

The research aims at developing a framework for testing systems such as closed-loop physiology management systems to ensure that they are safe and effective for use with patients. Building medical devices that are both robust and safe is a challenge. There has been a tremendous increase in modernization and innovation of various medical systems but many of these systems either fail trials or are recalled due to safety issues.

Medical operation rooms require care teams responsible for monitoring the patients and other technical surgical devices. The care process requires a balancing administration that takes care of the drugs and fluids …

Textured Contact Lens Based Iris Presentation Attack In Uncontrolled Environment, Daksha Yadav

Graduate Theses, Dissertations, and Problem Reports

The widespread use of smartphones has spurred the research in mobile iris devices. Due to their convenience, these mobile devices are also utilized in unconstrained outdoor conditions. At the same time, iris recognition in the visible spectrum has developed into an active area of research. These scenarios have necessitated the development of reliable iris recognition algorithms for such an uncontrolled environment. Additionally, iris presentation attacks such as textured contact lens pose a major challenge to current iris recognition systems.

Motivated by these factors, in this thesis, a detailed analysis of the effect of textured contact lenses on iris recognition in …

Virtual Reality Simulation Of Glenoid Reaming Procedure, Mohammadreza Faieghi

Electronic Thesis and Dissertation Repository

Glenoid reaming is a bone machining operation in Total Shoulder Arthroplasty (TSA) in which the glenoid bone is resurfaced to make intimate contact with implant undersurface. While this step is crucial for the longevity of TSA, many surgeons find it technically challenging. With the recent advances in Virtual Reality (VR) simulations, it has become possible to realistically replicate complicated operations without any need for patients or cadavers, and at the same time, provide quantitative feedback to improve surgeons' psycho-motor skills. In light of these advantages, the current thesis intends to develop tools and methods required for construction of a VR …

Modeling And Simulation Methodologies For Spinal Cord Stimulation., Saliya Kumara Kirigeeganage

Electronic Theses and Dissertations

The use of neural prostheses to improve health of paraplegics has been a prime interest of neuroscientists over the last few decades. Scientists have performed experiments with spinal cord stimulation (SCS) to enable voluntary motor function of paralyzed patients. However, the experimentation on the human spinal cord is not a trivial task. Therefore, modeling and simulation techniques play a significant role in understanding the underlying concepts and mechanics of the spinal cord stimulation. In this work, simulation and modeling techniques related to spinal cord stimulation were investigated. The initial work was intended to visualize the electric field distribution patterns in …

A Study Of Scalability And Cost-Effectiveness Of Large-Scale Scientific Applications Over Heterogeneous Computing Environment, Arghya K. Das

LSU Doctoral Dissertations

Recent advances in large-scale experimental facilities ushered in an era of data-driven science. These large-scale data increase the opportunity to answer many fundamental questions in basic science. However, these data pose new challenges to the scientific community in terms of their optimal processing and transfer. Consequently, scientists are in dire need of robust high performance computing (HPC) solutions that can scale with terabytes of data.

In this thesis, I address the challenges in three major aspects of scientific big data processing as follows: 1) Developing scalable software and algorithms for data- and compute-intensive scientific applications. 2) Proposing new cluster architectures …

The Human Keyboard, Derek Char, Thomas Chung, Alexander Mckee, Allen Pai

Interdisciplinary Design Senior Theses

Most products that implement features for user interactions utilize buttons or switches for the user to command to select actions to perform. Such designs are typically controlled with direct motions, such as touch or voice and are seldom designed in consideration of those unable to utilize direct control. In this project, we designed technology that reads naturally occuring biosignals from the body, which then can be apply those signals with any interface. For our specific application in this project, we decided to implement a keyboard. Instead of teaching the fingers how to type on a mechanical keyboard, the body can …

Dynamic Model For Simulating Motion Of The Right Ventricle, Brian Michael Larsen, Sam Koopman Porter, John Francis D'Ambrosio

Mechanical Engineering

This report documents all the research, ideation, and mockups used to determine right ventricle motion and develop a system capable of reproducing that motion on a tissue sample. The model is intended for evaluating anchoring systems being developed by Edwards Lifesciences for use with tricuspid valve therapies. Several design solutions were considered for the primary functions of recreating motion of the right ventricle and attaching tissue to the device. From these ideas a primary means of producing motion and attaching tissue was selected. These ideas were then developed over the course of a school year to become the final system …

Urinalysis Screening For Rural Communities, Dana Bren-Cardali, Lilian Dao, Jeffrey Destruel, Ryan Fernandez

Interdisciplinary Design Senior Theses

Access to medical care and health screenings is a necessity for patients around the globe, but it can be difficult to provide this without screenings becoming costly or convoluted. In rural and underdeveloped areas, patients are often disadvantaged when it comes to finding reliable and affordable healthcare. The isolation provided by their location and the rising costs of physicians makes it impossible for most impoverished communities to attain personalized care. Because of this, treatable diseases often go unaddressed, allowing diseases to progress to a critical condition. Mortality rates have shown to be higher in communities located in rural areas and …

Unsupervised Parkinson’S Disease Assessment, Alexander S. Adranly, Senbao Lu, Yousef Zoumot

Interdisciplinary Design Senior Theses

Parkinson’s Disease (PD) is a progressive neurological disease that affects 6.2 million people worldwide. The most popular clinical method to measure PD tremor severity is a standardized test called the Unified Parkinson’s Disease Rating Scale (UPDRS), which is performed subjectively by a medical professional. Due to infrequent checkups and human error introduced into the process, treatment is not optimally adjusted for PD patients. According to a recent review there are two devices recommended to objectively quantify PD symptom severity. Both devices record a patient’s tremors using inertial measurement units (IMUs). One is not currently available for over the counter purchases, …

Interactive Clinical Event Pattern Mining And Visualization Using Insurance Claims Data, Zhenhui Piao

Theses and Dissertations--Computer Science

With exponential growth on a daily basis, there is potentially valuable information hidden in complex electronic medical records (EMR) systems. In this thesis, several efficient data mining algorithms were explored to discover hidden knowledge in insurance claims data. The first aim was to cluster three levels of information overload(IO) groups among chronic rheumatic disease (CRD) patient groups based on their clinical events extracted from insurance claims data. The second aim was to discover hidden patterns using three renowned pattern mining algorithms: Apriori, frequent pattern growth(FP-Growth), and sequential pattern discovery using equivalence classes(SPADE). The SPADE algorithm was found to be the …

Characterization Of Language Cortex Activity During Speech Production And Perception, Hassan Baker

Electrical & Computer Engineering Theses & Dissertations

Millions of people around the world suffer from severe neuromuscular disorders such as spinal cord injury, cerebral palsy, amyotrophic lateral sclerosis (ALS), and others. Many of these individuals cannot perform daily tasks without assistance and depend on caregivers, which adversely impacts their quality of life. A Brain-Computer Interface (BCI) is technology that aims to give these people the ability to interact with their environment and communicate with the outside world. Many recent studies have attempted to decode spoken and imagined speech directly from brain signals toward the development of a natural-speech BCI. However, the current progress has not reached practical …