Engineering Commons^™

Identification And Characterization Of Two Novel Kcnh2 Mutations Contributing To Long Qt Syndrome, Anthony Owusu-Mensah, Jacqueline Treat, Joyce Bernardi, Ryan Pfeiffer, Robert Goodrow, Bright Tsevi, Victoria Lam, Michel Audette, Jonathan M. Cordeiro, Makarand Deo

Electrical & Computer Engineering Faculty Publications

We identified two different inherited mutations in KCNH2 gene, or human ether-a-go-go related gene (hERG), which are linked to Long QT Syndrome. The first mutation was in a 1-day-old infant, whereas the second was in a 14-year-old girl. The two KCNH2 mutations were transiently transfected into either human embryonic kidney (HEK) cells or human induced pluripotent stem-cell derived cardiomyocytes. We performed associated multiscale computer simulations to elucidate the arrhythmogenic potentials of the KCNH2 mutations. Genetic screening of the first and second index patients revealed a heterozygous missense mutation in KCNH2, resulting in an amino acid change (P632L) in the …

Cad System For Early Diagnosis Of Diabetic Retinopathy Based On 3d Extracted Imaging Markers., Ahmed Sleman

Electronic Theses and Dissertations

This dissertation makes significant contributions to the field of ophthalmology, addressing the segmentation of retinal layers and the diagnosis of diabetic retinopathy (DR). The first contribution is a novel 3D segmentation approach that leverages the patientspecific anatomy of retinal layers. This approach demonstrates superior accuracy in segmenting all retinal layers from a 3D retinal image compared to current state-of-the-art methods. It also offers enhanced speed, enabling potential clinical applications. The proposed segmentation approach holds great potential for supporting surgical planning and guidance in retinal procedures such as retinal detachment repair or macular hole closure. Surgeons can benefit from the accurate …

Quantum Computing And Its Applications In Healthcare, Vu Giang

OUR Journal: ODU Undergraduate Research Journal

This paper serves as a review of the state of quantum computing and its application in healthcare. The various avenues for how quantum computing can be applied to healthcare is discussed here along with the conversation about the limitations of the technology. With more and more efforts put into the development of these computers, its future is promising with the endeavors of furthering healthcare and various other industries.

Prepubertal Periodontitis In Children: For An Adequate Diagnosis And Optimal Care, F.Z. El Mouatarif, S. Chemlali, M. Hamza, J. Kissa, S. El Arabi

Health Sciences

Prepubertal periodontitis (PP) is a rare and rapid progressive condition found a young cohort of patients that results in destruction of the periodontal support of the primary dentition. Its generalized form, prepubertal periodontitis is often associated with a significant gingival tissue inflammation and fast bone loss with attachment loss leading to the tooth loss. The localized form of PP is characterized by a much more discreet inflammation and slow evolution. It can be associated with a known underlying systemic disease or may occur as part of a recognized syndrome or as an isolated finding. Different treatment modalities can be used …

A Type-2 Fuzzy Rule-Based Model For Diagnosis Of Covid-19, İhsan Şahi̇n, Erhan Akdoğan, Mehmet Emi̇n Aktan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a type-2 fuzzy logic-based decision support system comprising clinical examination and blood test results that health professionals can use in addition to existing methods in the diagnosis of COVID-19 has been developed. The developed system consists of three fuzzy units. The first fuzzy unit produces COVID-19 positivity as a percentage according to the respiratory rate, loss of smell, and body temperature values, and the second fuzzy unit according to the C-reactive protein, lymphocyte, and D-dimer values obtained as a result of the blood tests. In the third fuzzy unit, the COVID-19 positivity risks according to the clinical …

A Study Of Heart Disease Diagnosis Using Machine Learning And Data Mining, Intisar Ahmed

Electronic Theses, Projects, and Dissertations

Heart disease is the leading cause of death for people around the world today. Diagnosis for various forms of heart disease can be detected with numerous medical tests, however, predicting heart disease without such tests is very difficult. Machine learning can help process medical big data and provide hidden knowledge which otherwise would not be possible with the naked eye. The aim of this project is to explore how machine learning algorithms can be used in predicting heart disease by building an optimized model. The research questions are; 1) What Machine learning algorithms are used in the diagnosis of heart …

Focused Ultrasound-Enabled Blood-Based Liquid Biopsy (Sonobiopsy) For Brain Disease Diagnosis, Christopher Pham Pacia

McKelvey School of Engineering Theses & Dissertations

Brain cancer severely threatens human health due to its disruption of neurological function, poor prognosis, and substantial reduction in quality of life. Glioblastoma (GBM) is the most devastating brain cancer; not only is it the most common malignant primary tumor in adults, but also it has a median survival of 14 months with a 5-year survival rate of less than 5%. Despite advances in multidisciplinary treatment that includes surgical resection, radiation therapy, and chemotherapy, almost all patients experience tumor progression and nearly universal mortality within 2 years. However, advances in patient care have suggested that the accurate diagnosis of molecular …

Role Of Machine Learning In Early Diagnosis Of Kidney Diseases., Mohamed Nazih Mohamed Ibrahim Shehata

Electronic Theses and Dissertations

Machine learning (ML) and deep learning (DL) approaches have been used as indispensable tools in modern artificial intelligence-based computer-aided diagnostic (AIbased CAD) systems that can provide non-invasive, early, and accurate diagnosis of a given medical condition. These AI-based CAD systems have proven themselves to be reproducible and have the generalization ability to diagnose new unseen cases with several diseases and medical conditions in different organs (e.g., kidneys, prostate, brain, liver, lung, breast, and bladder). In this dissertation, we will focus on the role of such AI-based CAD systems in early diagnosis of two kidney diseases, namely: acute rejection (AR) post …

Evaluation Of Selected Computer Software For Concussion Recovery And Diagnosis, J.P. Jensen

Honors Theses

Acquired traumatic brain injuries, such as concussions, impact many athletes participating in sports, particularly at the high school, collegiate, and professional levels. The risks posed by concussions – particularly when an athlete suffers repeated injuries – demands that protocols and tools be developed to maximize athlete health and safety. Computer technology can perform critical roles in the analysis and management of concussions. While specialized devices in the areas of imaging and impact sensing, are most associated with concussion management, researchers within the last two decades have increasingly explored the incorporation of various consumer technologies into the identification and treatment of …

Alpha Synuclein: A Therapeutic Target And Biomarker For Parkinson’S Disease, Max Chase

USF Tampa Graduate Theses and Dissertations

Parkinson’s Disease is the second most common neurodegenerative disease after Alzheimer’s Disease, and the most common motor disorder. In fact, nearly a third of those with AD have PD. A major hallmark of PD is the appearance of Lewy Bodies, proteinaceous cytoplasm inclusions, that build up and spread throughout the CNS in a prion like fashion. The major component of these Lewy Bodies is a protein called alpha-synuclein. Alpha-syn is a 14kDa protein made of 140 amino acids and found in the presynaptic ends of CNS neurons, acting as a chaperone and regulator. The protein is also found in the …

An Ensemble Approach For Patient Prognosis Of Head And Neck Tumor Using Multimodal Data, Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, Mohammad Yaqub

Computer Vision Faculty Publications

Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Tradi-tional machine learning algorithms have been eminently useful in crafting prognostic models in the last few decades. Recently, deep learning algorithms have shown significant improvement when developing diag-nosis and prognosis solutions to different healthcare problems. However, most of these solutions rely solely on either imaging or clinical data. Utilizing patient tabular data such as demographics and patient med-ical history alongside imaging data in a multimodal approach to solve a prognosis task has started to gain more interest recently and …

Neuromotor Changes In Participants With A Concussion History Can Be Detected With A Custom Smartphone App, Christopher K. Rhea, Masahiro Yamada, Nikita A. Kuznetsov, Jason T. Jakiela, Chanel T. Lojacono, Scott E. Ross, F. J. Haran, Jason M. Bailie, W. Geoffrey Wright

Rehabilitation Sciences Faculty Publications

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between …

3d Printing In Cardiology: A Review Of Applications And Roles For Advanced Cardiac Imaging, Ellen M. Lindquist, Jordan M. Gosnell, Sana K. Khan, John L. Byl, Weihua Zhou, Jingfeng Jiang, Et. Al.

Michigan Tech Publications

With the rate of cardiovascular diseases in the U.S increasing throughout the years, there is a need for developing more advanced treatment plans that can be tailored to specific patients and scenarios. The development of 3D printing is rapidly gaining acceptance into clinical cardiology.

In this review, key technologies used in 3D printing are briefly summarized, particularly, the use of artificial intelligence (AI), open-source tools like MeshLab and MeshMixer, and 3D printing techniques such as fused deposition molding (FDM) and polyjet are reviewed. The combination of 3D printing, multiple image integration, and augmented reality may greatly enhance data visualization …

A Simple, Realistic Walled Phantom For Intravascular And Intracardiac Applications., Hareem Nisar, John Moore, Roberta Piazza, Efthymios Maneas, Elvis C S Chen, Terry M Peters

Robarts Imaging Publications

PURPOSE: This work aims to develop a simple, anatomically and haptically realistic vascular phantom, compatible with intravascular and intracardiac ultrasound. The low-cost, dual-layered phantom bridges the gap between traditional wall-only and wall-less phantoms by showing both the vessel wall and surrounding tissue in ultrasound imaging. This phantom can better assist clinical tool training, testing of intravascular devices, blood flow studies, and validation of algorithms for intravascular and intracardiac surgical systems.

METHODS: Polyvinyl alcohol cryogel (PVA-c) incorporating a scattering agent was used to obtain vessel and tissue-mimicking materials. Our specific design targeted the inferior vena cava and renal bifurcations which were …

Spatial Heterogeneity Utilization In Ct Images For Lung Nodule Classication, Dmitrii Cherezov

USF Tampa Graduate Theses and Dissertations

Lung cancer (LC) is leading in the number of deaths among the other types of cancer. According to the American Cancer Society, 135,720 deaths during 2020 in the USA will be associated with LC. The patient 5-year survival rate of 16\% was reported in 1986 and 19% in 2019. One of the reasons why survival rate remains low is that the majority of patients diagnosed with cancer had stages III and IV. In contrast, a 5-year survival rate of 70% was reported for patients of stage IA after surgical resection in the National Lung Screening Trial.

CT screening detects a …

A Bibliometric Survey On The Diagnosis Of Plant Leaf Diseases Using Artificial Intelligence, Rutuja Rajendra Patil, Sumit Kumar Dr

Library Philosophy and Practice (e-journal)

Due to uncertain environmental conditions such as untimely rainfall, hailstorms, draught, fog the agriculture sector faces huge loss in crop yield. One of the biggest reason is plant leaf diseases. Therefore the need arises to diagnose the plant leaf diseases beforehand so that the diseases could be avoided and crop yield loss could be minimized. The paper represents the bibliometric study of plant leaf disease diagnosis using Artificial Intelligence. The study focuses on 472 scientific documents such as journals, articles, book chapters publicized in various journals. These documents are extracted from Scopus database after querying it with keywords related to …

Estudio Prospectivo Al Año 2040 Para La Finca Palmicultora "El Diamante" Ubicada En El Municipio De San Carlos De Guaroa - Meta, María Camila Rodríguez Galvis

Ingeniería Industrial

Este trabajo de grado tiene como objetivo desarrollar un estudio de prospectiva estratégica para la finca “El Diamante” empleando diferentes herramientas las cuales permitirán tener las estrategias necesarias para alcanzar los objetivos planteados hacia el año 2040, tomando como punto de partida la situación actual, el entorno en el que se desenvuelven y su competencia, todo esto, para tener claridad y lograr localizar su propio mercado durante los próximos años. El proyecto consta de 13 capítulos, los cuales se presentarán a continuación.

En el capítulo 1 se explicará el planteamiento del problema y se presenta el estado actual de la …

Diagnosis On Expansion Of Heat-Cured Precast Concrete Blocks Due To Delayed Ettringite Formation In Japan, Yuichiro Kawabata

International Conference on Durability of Concrete Structures

Delayed ettringite formation (DEF) in concrete causes internal swelling, which reduces the mechanical properties of concrete and can lead to issues with concrete structures due to potentially large expansive deformation. In order to address the issues of DEF-affected structures, proper assessment of the structures affected is important. However, petrographic diagnosis of concrete affected by DEF remains a controversial issue. In this paper, as case studies, diagnosis on precast concrete blocks suspected of experiencing DEF was carried out. The concrete blocks were made of white Portland cement, limestone gravel, and limestone sand mixed with copper slag. The blocks were excessively heat-cured …

Internal Fault Diagnosis Of Mmc-Hvdc Based On Classification Algorithms In Machine Learning, Tianyi Jin

Theses and Dissertations

With the development of the HVDC system, MMC-HVDC is now the most advanced technology that has been put into use. In power systems, faults happen during the operation due to natural reasons or devices physical issues, which would cause serious economic losses and other implications. Thus, fault detection and analysis are extremely important, especially in the HVDC system. Existing works in literature mainly focus on the faults detection and analysis on the system side such as short circuit of the AC side, and open circuit of the DC side. However, little attention has been paid to the fault detection and …

Internal Fault Diagnosis Of Mmc-Hvdc Based On Classification Algorithms In Machine Learning, Tianyi Jin

Theses and Dissertations

With the development of the HVDC system, MMC-HVDC is now the most advanced technology that has been put into use. In power systems, faults happen during the operation due to natural reasons or devices physical issues, which would cause serious economic losses and other implications. Thus, fault detection and analysis are extremely important, especially in the HVDC system. Existing works in literature mainly focus on the faults detection and analysis on the system side such as short circuit of the AC side, and open circuit of the DC side. However, little attention has been paid to the fault detection and …

Rapid Separation Of Bacteria From Blood For Sepsis Diagnosis, Mahsa Alizadeh

Theses and Dissertations

Sepsis is a severe blood infection caused by bacteria entering the blood stream. Sepsis caused by antibiotic resistant bacteria is very dangerous with a high mortality rate. The current clinical diagnostic methods for sepsis require culturing the blood sample prior to other steps of the diagnosis procedure. Culturing the blood samples is a time-consuming step which increases the time required for the diagnostic procedure. Considering the fact that the mortality rate of the sepsis increases as time passes, it is essential to find methods for sepsis diagnosis that do not require culturing the samples. The first step of a new …

A Psychopathological Approach To Safety Engineering In Ai And Agi, Vahid Behzadan, Arslan Munir, Roman V. Yampolskiy

Faculty Scholarship

The complexity of dynamics in AI techniques is already approaching that of complex adaptive systems, thus curtailing the feasibility of formal controllability and reachability analysis in the context of AI safety. It follows that the envisioned instances of Artificial General Intelligence (AGI) will also suffer from challenges of complexity. To tackle such issues, we propose the modeling of deleterious behaviors in AI and AGI as psychological disorders, thereby enabling the employment of psychopathological approaches to analysis and control of misbehaviors. Accordingly, we present a discussion on the feasibility of the psychopathological approaches to AI safety, and propose general directions for …

Methodological Aspects Of Continuous Controlling And Diagnostics Traction Electrical Equipments Using Methods Of Spectral Analysis, M.S Yakubov, Z.G Muxamedova, U.Sh Isroilov, J.S Fayzullaev

Chemical Technology, Control and Management

The work shows the high efficiency of diagnosing electrical equipment using the modulated stator current of electrical machines associated with rotor defects, with the presence of interturn and interphase closures, the vibriation-diagnostic parameters of their bearings, as well as the harmonic components of combinational frequencies and pulsations, appearing but for the non-linear volt-amperic characteristics of traction transformer and for the converters of electric locomotives. The scheme of integral informational environment of continuous diagnostics of electric devices of railway energetics was given.

Optical Coherence Tomography Application To Alopecia In The Scalp, Elizabeth Melcher

Research Opportunities for Engineering Undergraduates (ROEU) Program 2017-18

Alopecia is the loss of hair, whether it be from the scalp or other regions of the body. Current techniques used to best diagnose and track alopecia are often invasive, requiring a biopsy for results. The use of the OCT, or optical coherence tomography, could drastically improve a patient’s experience in undergoing a diagnosis while proving accurate results. The objective of this study is to develop diagnostic algorithms for the rapid, non-invasive diagnosis of alopecia with OCT. The first step is collecting OCT images of a healthy scalp to understand the anatomical structures with the imaging technique.

Diagnosis Of Reverse Osmosis Desalination Water System Using Bond Graph Approach, Abderrahmene Sallami, Dhia Mzoughi, Abdelkader Mami

Turkish Journal of Electrical Engineering and Computer Sciences

Industrial systems have become quite complicated. It is therefore necessary to look for a reliable supervision system to properly treat the information and make the appropriate decision to stop the system or leave it in operation. Supervision of automated systems goes to the heart of the matter. This paper concerns the design of a new methodology for diagnosis based on bond graph modeling. We apply a diagnostic method by Luenberger observer using the bond graph approach on a desalination unit. Tests are carried out on the water input pressure delivered by the pump and the output flow rates of the …

Fuzzy Color Clustering For Melanoma Diagnosis In Dermoscopy Images, Haidar A. Almubarak, R. Joe Stanley, William V. Stoecker, Randy Hays Moss

Electrical and Computer Engineering Faculty Research & Creative Works

A fuzzy logic-based color histogram analysis technique is presented for discriminating benign skin lesions from malignant melanomas in dermoscopy images. The approach extends previous research for utilizing a fuzzy set for skin lesion color for a specified class of skin lesions, using alpha-cut and support set cardinality for quantifying a fuzzy ratio skin lesion color feature. Skin lesion discrimination results are reported for the fuzzy clustering ratio over different regions of the lesion over a data set of 517 dermoscopy images consisting of 175 invasive melanomas and 342 benign lesions. Experimental results show that the fuzzy clustering ratio applied over …

Pediatric Leukemia: Diagnosis To Treatment–A Review, Samantha C. Bernard, Ehab H. Abdelsamad, Paisley A. Johnson, Daniel L. Chapman, Madhukiran Parvathaneni

Faculty Works

Leukemia is cancer of the blood and bone marrow, it is the most common cancer found in children and is found to be more than one fourth of pediatric cancers. It causes white blood cells to become abnormal and the body to become weak. This deficiency in the immune system reduces the body's ability to fight infection or simple airborne illnesses, causing extensive treatment of common pathogens and cancer treatment. The present review covers all topics, from diagnosis to treatment of pediatric leukemia, as well as the stages of growth and physiological changes throughout the process. As leukemia has a …

Label-Free Raman Imaging To Monitor Breast Tumor Signatures, John Ciubuc

Open Access Theses & Dissertations

Methods built on Raman spectroscopy have shown major potential in describing and discriminating between malignant and benign specimens. Accurate, real-time medical diagnosis benefits in substantial improvements through this vibrational optical method. Not only is acquisition of data possible in milliseconds and analysis in minutes, Raman allows concurrent detection and monitoring of all biological components. Besides validating a significant Raman signature distinction between non-tumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, this study reveals a label-free method to assess overexpression of epidermal growth factor receptors (EGFR) in tumor cells. EGFR overexpression sires Raman features associated with phosphorylated threonine and serine, and …

Iris Nevus Diagnosis: Convolutional Neural Network And Deep Belief Network, Oyebade Oyedotun, Adnan Khashman

Turkish Journal of Electrical Engineering and Computer Sciences

This work presents the diagnosis of iris nevus using a convolutional neural network (CNN) and deep belief network (DBN). Iris nevus is a pigmented growth (tumor) found in the front of the eye or around the pupil. It is seen that racial and environmental factors affect the iris color (e.g., blue, hazel, brown) of patients; hence, pigmented growths may be masked in the eye background or iris. In this work, some image processing techniques are applied to images to reinforce areas of interests in them, after which the considered classifiers are trained. We describe the automated diagnosis of iris nevus …

Portable Motion Lab For Diagnostic And Rehabilitation Processes, Yogesh Laxman Chavan

Browse all Theses and Dissertations

In this thesis research, we have explored the capabilities of a household body-tracking device - Microsoft Xbox Kinect for motion analysis and assessment to assist patient’s rehabilitation after joint replacement and repair surgeries. In particular, we have combined the motion tracking capabilities of Kinect with the 3D modelling of human body for accurate and intuitive movement assessment and feedback. Our prototype system demonstrates the effective and efficient workflow of motion capturing, data processing and analyzing and augmented reality based presentation, resulting in a design which is not only accurate, reliable and robust, but also extremely cost- and space-efficient. Furthermore, we …