Engineering Commons^™

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Heart Disease Prediction Using Stacking Model With Balancing Techniques And Dimensionality Reduction, Ayesha Noor, Nadeem Javaid, Nabil Alrajeh, Babar Mansoor, Ali Khaqan, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Heart disease is a serious worldwide health issue with wide-reaching effects. Since heart disease is one of the leading causes of mortality worldwide, early detection is crucial. Emerging technologies like Machine Learning (ML) are currently being actively used by the biomedical, healthcare, and health prediction industries. PaRSEL, a new stacking model is proposed in this research, that combines four classifiers, Passive Aggressive Classifier (PAC), Ridge Classifier (RC), Stochastic Gradient Descent Classifier (SGDC), and eXtreme Gradient Boosting (XGBoost), at the base layer, and LogitBoost is deployed for the final predictions at the meta layer. The imbalanced and irrelevant features in the …

Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical …

Seeing The Big Picture: System Architecture Trends In Endoscopy And Led-Based Hyperspectral Subsystem Intergration, Craig M. Browning

<strong> Theses and Dissertations </strong>

Early-stage colorectal lesions remain difficult to detect. Early development of neoplasia tends to be small (less than 10 mm) and flat and difficult to distinguish from surrounding mucosa. Additionally, optical diagnosis of neoplasia as benign or malignant is problematic. Low rates of detection of these lesions allow for continued growth in the colorectum and increased risk of cancer formation. Therefore, it is crucial to detect neoplasia and other non-neoplastic lesions to determine risk and guide future treatment. Technology for detection needs to enhance contrast of subtle tissue differences in the colorectum and track multiple biomarkers simultaneously. This work implements one …

Evaluation Of Root-End Resection With Conventional And Ultrasonic Methods: A Single-Blind, Randomized In-Vitro Study, Mohammad Al Shammaa, Roula S. Abiad, Nayer Abo Elsaad

BAU Journal - Creative Sustainable Development

The root-end resection is considered critical endodontic surgical procedure. Three millimeters of the root tip is resected and root-end cavity with parallel walls and comparable depth is cut to receive a root-end filling. The literature discussed dentinal cracks after root canal instrumentation and/or root dentine cutting. The aim of the present study was to assess cracks at root ends after resection with conventional versus ultrasonic techniques. Material and Methodology: Thirty-two extracted human lower premolar teeth with single root were used. Their root canals were prepared and received gutta-percha. Sixteen roots Group 1 were resected using tungsten carbide fissure burs, while …

Aptamer-Based Voltammetric Biosensing For The Detection Of Codeine And Fentanyl In Sweat And Saliva, Rosa Lashantez Cromartie

FIU Electronic Theses and Dissertations

Despite the many governmental and medicinal restrictions created to combat the opioid epidemic in the United States, opioid abuse and overdose rates continue to rise. The development of an aptamer-based voltammetric sensor and biosensor is described in this dissertation. The aim was to develop a low-cost, sensitive, and specific aptamer-based sensor for on-site, label-free determination of codeine and fentanyl in biological fluids. To do this, the surfaces of screen-printed carbon electrodes (SPCE) were modified with gold nanoparticles (AuNPs), followed by the addition of single-stranded DNA aptamers. These were covalently bound to the electrode surface. Operations of the sensors were collected …

Pulmon-C: A Real-Time Monitoring Framework Of Pulmonary Function, Md Saiful Islam, Maria Valero, Shahriar Hossain

Symposium of Student Scholars

This project will develop PulMon-C, a real-time monitoring framework of pulmonary function to diagnose COVID-19 patients who are being self-quarantined at home. The tool will identify anomalies in breathe rate and predict pulmonary deterioration to raise alert for immediate actions. The uniqueness of the tool is using non-invasive sensors placed under-mattress that are able to communicate data about the respiratory signal. The customer segment of PulMon-C will be the diagnosed COVID-19 patients and healthcare providers. PulMon-C will assist with the remote monitoring of COVID-19 patients as an urgent need in the USA and will bring larger impact in delivering …

Optimal Analytical Methods For High Accuracy Cardiac Disease Classification And Treatment Based On Ecg Data, Jianwei Zheng

Computational and Data Sciences (PhD) Dissertations

This work constitutes six projects. In the first project, a newly inaugurated research database for 12-lead electrocardiogram signals was created under the auspices of Chapman University and Shaoxing People's Hospital (Shaoxing Hospital Zhejiang University School of Medicine). This database aims to enable the scientific community in conducting new studies on arrhythmia and other cardiovascular conditions. In the second project, we created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract …

Zein And Lignin-Based Nanoparticles As Delivery Systems: Pesticide Release And Nanoparticle Health Impact On Soybean Plants, Fallon Polette Salinas Gonzalez

LSU Doctoral Dissertations

This research examined the effect of biodegradable, polymeric, lignin-based nanoparticles (LNPs, 113.8±3.4, negatively charged) and zein nanoparticles (ZNP, 141.6±3.9, positively charged) on soybean plant health. The LNPs were synthesized from lignin, covalently linked to poly(lactic-co-glycolic) acid by emulsion evaporation. ZNPs were synthesized by nanoprecipitation. Soybeans grown hydroponically were treated with three concentrations (0.02, 0.2, and 2 mg/ml) of NPs at 28 days after germination. The effect of ZNPs and LNPs on plant health was determined through analysis of root and stem length, chlorophyll concentration, dry biomass of roots and stem, as well as carbon, nitrogen, and micronutrient absorption after 1, …

The Enlightening Role Of Explainable Artificial Intelligence In Chronic Wound Classification, Salih Sarp, Murat Kuzlu, Emmanuel Wilson, Umit Cali, Ozgur Guler

Engineering Technology Faculty Publications

Artificial Intelligence (AI) has been among the most emerging research and industrial application fields, especially in the healthcare domain, but operated as a black-box model with a limited understanding of its inner working over the past decades. AI algorithms are, in large part, built on weights calculated as a result of large matrix multiplications. It is typically hard to interpret and debug the computationally intensive processes. Explainable Artificial Intelligence (XAI) aims to solve black-box and hard-to-debug approaches through the use of various techniques and tools. In this study, XAI techniques are applied to chronic wound classification. The proposed model classifies …

Nebulizer-Based Systems To Improve Pharmaceutical Aerosol Delivery To The Lungs, Benjamin M. Spence

Theses and Dissertations

Combining vibrating mesh nebulizers with additional new technologies leads to substantial improvements in pharmaceutical aerosol delivery to the lungs across therapeutic administration methods. In this dissertation, streamlined components, aerosol administration synchronization, and/or Excipient Enhanced Growth (EEG) technologies were utilized to develop and test several novel devices and aerosol delivery systems. The first focus of this work was to improve the poor delivery efficiency, e.g., 3.6% of nominal dose (Dugernier et al. 2017), of aerosolized medication administration to adult human subjects concurrent with high flow nasal cannula (HFNC) therapy, a form of continuous-flow non-invasive ventilation (NIV). The developed Low-Volume Mixer-Heater (LVMH) …

Impact Of Hemodynamic Vortex Spatial And Temporal Characteristics On Analysis Of Intracranial Aneurysms, Kevin W. Sunderland

Dissertations, Master's Theses and Master's Reports

Subarachnoid hemorrhage is a potentially devastating pathological condition in which bleeding occurs into the space surrounding the brain. One of the prominent sources of subarachnoid hemorrhage are intracranial aneurysms (IA): degenerative, irregular expansions of area(s) of the cerebral vasculature. In the event of IA rupture, the resultant subarachnoid hemorrhage ends in patient mortality occurring in ~50% of cases, with survivors enduring significant neurological damage with physical or cognitive impairment. The seriousness of IA rupture drives a degree of clinical interest in understanding these conditions that promote both the development and possible rupture of the vascular malformations. Current metrics for the …

3d Reconstruction Of Spine Image From 2d Mri Slices Along One Axis, Somoballi Ghoshal, Sourav Banu, Amlan Chakrabarti, Susmita Sur-Kolay, Alok Pandit

Journal Articles

Magnetic resonance imaging (MRI) is a very effective method for identifying any abnormality in the structure and physiology of the spine. However, MRI is time consuming as well as costly. In this work, the authors propose an algorithm which can reduce the time of MRI and thus the cost, with minimal compromise on accuracy. They reconstruct a three-dimensional (3D) image of the spine from a sequence of 2D MRI slices along any one axis with reasonable slice gap. In order to preserve the image at the edges properly, they regenerate the 3D image by using a combination of bicubic and …

Face Mask Effects Of Co2, Heart Rate, Respiration Rate, And Oxygen Saturation On Instructor Pilots, Andrew R. Dattel, Nicola M. O'Toole, Guillermina Lopez, Kenneth P. Byrnes

Publications

The COVID-19 pandemic has required people to take new measures to mitigate the spread of the communicable virus. Guidelines from health organizations, government offices, and universities have been disseminated. Adherence to these guidelines cannot be more critical for flight training. This study explored the effects face masks had on CO2, heart rate, respiration rate, and oxygen saturation while wearing a face mask at an oxygen level simulated to 5,000 feet. Thirty-two instructor pilots (IP) volunteered to participate in the study. IPs spent 90 minutes in a normobaric chamber while wearing a cloth face mask or a paper face mask. Participants …

Prediction Of Molecular Mutations In Diffuse Low-Grade Gliomas Using Mr Imaging Features, Zeina A. Shboul, James Chen, Khan M. Iftekharrudin

Electrical & Computer Engineering Faculty Publications

Diffuse low-grade gliomas (LGG) have been reclassified based on molecular mutations, which require invasive tumor tissue sampling. Tissue sampling by biopsy may be limited by sampling error, whereas non-invasive imaging can evaluate the entirety of a tumor. This study presents a non-invasive analysis of low-grade gliomas using imaging features based on the updated classification. We introduce molecular (MGMT methylation, IDH mutation, 1p/19q co-deletion, ATRX mutation, and TERT mutations) prediction methods of low-grade gliomas with imaging. Imaging features are extracted from magnetic resonance imaging data and include texture features, fractal and multi-resolution fractal texture features, and volumetric features. Training models include …

Towards Stable Electrochemical Sensing For Wearable Wound Monitoring, Sohini Roychoudhury

FIU Electronic Theses and Dissertations

Wearable biosensing has the tremendous advantage of providing point-of-care diagnosis and convenient therapy. In this research, methods to stabilize the electrochemical sensing response from detection of target biomolecules, Uric Acid (UA) and Xanthine, closely linked to wound healing, have been investigated. Different kinds of materials have been explored to address such detection from a wearable, healing platform. Electrochemical sensing modalities have been implemented in the detection of purine metabolites, UA and Xanthine, in the physiologically relevant ranges of the respective biomarkers. A correlation can be drawn between the concentrations of these bio-analytes and wound severity, thus offering probable quantitative insights …

Data Visualization Of Treatment Outcomes For Tuberculosis Patients, Joy Jenkins

Industrial Engineering Undergraduate Honors Theses

Tuberculosis is an infectious disease, and different treatments have been discovered over the years. However, patients may develop various drug resistance levels that affect the likelihood of becoming cured or dying. In this study, we sought to employ data visualization to explore the relationship between treatment trajectory, as indicated by smear and culture results in the follow-up tests and patient outcomes. A large sample of patients have been broken down by demographics including age, gender, and drug resistance status. Sankey diagrams were used to visualize the pathway progression of the patients over time split between two time periods- months 0-6 …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

Applications Of Supervised Machine Learning In Autism Spectrum Disorder Research: A Review, Kayleigh K. Hyde, Marlena N. Novack, Nicholas Lahaye, Chelsea Parlett-Pelleriti, Raymond Anden, Dennis R. Dixon, Erik Linstead

Engineering Faculty Articles and Research

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing ASD, exploring its genetic underpinnings, and designing effective interventions. This paper provides a comprehensive review of 45 papers utilizing supervised machine learning in ASD, including algorithms for classification and text analysis. The goal of the paper is to identify and describe supervised machine learning trends in ASD literature as …

Investigation Of Zebrafish Larvae Behavior As Precursor For Suborbital Flights: Feasibility Study, Pedro Llanos, Kristina Andrijauskaite, Mark Rubinstein, Sherine S.L. Chan

Pedro J. Llanos (www.AstronauticsLlanos.com)

Surgical And Medical Applications Of Drones: A Comprehensive Review, Brent Terwilliger, James C. Rosser Jr., Vudatha Vignesh, Brett C. Parker

Publications

Drones have the ability to gather real time data cost effectively, to deliver payloads and have initiated the rapid evolution of many industrial, commercial, and recreational applications. Unfortunately, there has been a slower expansion in the field of medicine. This article provides a comprehensive review of current and future drone applications in medicine, in hopes of empowering and inspiring more aggressive investigation.

Effects Of 8-Week Sensory Electrical Stimulation Combined With Motor Training On Eeg-Emg Coherence And Motor Function In Individuals With Stroke, Li-Ling Hope Pan, Wen-Wen Yang, Mei-Wun Tsai, Shun-Hwa Wei, Felipe Fregni, Vincent Chiun-Fan Chen, Li-Wei Chou

Engineering Science Faculty Publications

The peripheral sensory system is critical to regulating motor plasticity and motor recovery. Peripheral electrical stimulation (ES) can generate constant and adequate sensory input to influence the excitability of the motor cortex. The aim of this proof of concept study was to assess whether ES prior to each hand function training session for eight weeks can better improve neuromuscular control and hand function in chronic stroke individuals and change electroencephalography-electromyography (EEG-EMG) coherence, as compared to the control (sham ES). We recruited twelve subjects and randomly assigned them into ES and control groups. Both groups received 20-minute hand function training twice …

Design Of A Homeopathic Solution For Chronic Cough, Jacob Ziemke

Senior Honors Projects, 2010-2019

Chronic cough is most commonly defined as a cough that persists for more than eight weeks and is estimated to affect more than 30 million people in the United States at any given time. Diseases contributing to the onset of chronic cough include asthma, pulmonary fibrosis, lung cancer, postnasal drip, gastroesophageal reflux disease (GERD), and bronchitis, and may include lifestyle choices such as smoking. For those who seek medical advice, pharmaceuticals and speech therapy are two common methods of combating chronic cough but serve to mask the symptoms rather than treat the problem; frequently, chronic cough is misdiagnosed or cannot …

A Study Of Acoustically Activated Nanodroplets, Songita Choudhury

Theses & Dissertations

Current treatment of acute myocardial infarction (AMI), which is the main pathophysiological event leading to death in the United States, has advanced considerably with the introduction of emergent percutaneous interventions, but there remains an urgent need for novel techniques to rapidly and accurately detect infarcted or ischemic tissue that results from AMI. Ultrasound contrast agents, also known as microbubbles (MB), have become commonplace in echocardiography. However, MBs are purely intravascular tracers and unable to cross endothelial barriers due to size. The limitations of MBs, namely size and short circulation times within the human body, led to the development of phase-change …

Detection Of Leukocytes Stained With Acridine Orange Using Unique Spectral Features Acquired From An Image-Based Spectrometer, Courtney J. Hunter

Biomedical Engineering Undergraduate Honors Theses

A leukocyte differential count can be used to diagnosis a myriad blood disorders, such as infections, allergies, and efficacy of disease treatments. In recent years, attention has been focused on developing point-of-care (POC) systems to provide this test in global health settings. Acridine orange (AO) is an amphipathic, vital dye that intercalates leukocyte nucleic acids and acidic vesicles. It has been utilized by POC systems to identify the three main leukocyte subtypes: granulocytes, monocytes, and lymphocytes. Subtypes of leukocytes can be characterized using a fluorescence microscope, where the AO has a 450 nm excitation wavelength and has two peak emission …

Optical Imaging Of Metabolic Adaptability As A Biomarker For Metastatic Potential In Breast Cancer Cells, Mason G. Harper

Biomedical Engineering Undergraduate Honors Theses

Breast cancer metastasis is the main cause for mortality in breast cancer patients. However, knowledge of metastatic recurrence is limited, and there is a need to understand metastatic recurrence in order to treat breast cancer patients more effectively. Highly invasive metastatic breast cancer has shown to exhibit metabolic adaptability, transitioning from glycolysis to oxidative phosphorylation in the presence of microenvironmental stress. NADH and FAD are naturally occurring cofactor products during glycolysis and oxidative phosphorylation, respectively, and they are of particular importance during these metabolic processes due to their endogenous fluorescence. Measuring the ratio of fluorescence intensities of these cofactors through …

Design Of Radio-Frequency Arrays For Ultra-High Field Mri, Ian R O Connell

Electronic Thesis and Dissertation Repository

Magnetic Resonance Imaging (MRI) is an indispensable, non-invasive diagnostic tool for the assessment of disease and function. As an investigational device, MRI has found routine use in both basic science research and medicine for both human and non-human subjects.

Due to the potential increase in spatial resolution, signal-to-noise ratio (SNR), and the ability to exploit novel tissue contrasts, the main magnetic field strength of human MRI scanners has steadily increased since inception. Beginning in the early 1980’s, 0.15 T human MRI scanners have steadily risen in main magnetic field strength with ultra-high field (UHF) 8 T MRI systems deemed to …

Characterization Of Left-Ventricular Thrombus Formation Using High Frequency Ultrasound, Kelsey A. Bullens, Arvin H. Soepriatna, Pavlos P. Vlachos, Craig J. Goergen

The Summer Undergraduate Research Fellowship (SURF) Symposium

Heart failure is a leading cause of death in the United States, and cardiac thrombus, a common morbidity associated with heart failure, significantly increases a patient’s risk of embolic events. The objective of this project is to characterize left-ventricular (LV) thrombus development using high frequency ultrasound imaging in a murine model. C57BL/6J wild-type mice (n=6) were injected intraperitoneally with iron dextran five times a week for six weeks to increase oxidative stress in the heart. Granulocyte-colony stimulating factor (G-CSF) was subcutaneously injected daily during the second week to initiate stem cell migration and stimulate endothelial cell activation, thus increasing the …

Control System For 3d Printable Robotic Hand, Htoo Wai Htet

Honors Theses

Humanoid robotics is a growing area of research due to its potential applications in orthosis and prosthesis for human beings. With the currently available technologies, the most advanced robotic hands used in prosthetics or robotics can cost from $11,000 to $90,000, making it inaccessible to the general population of amputees and robotics hobbyists. Most of the features provided by these expensive technologies are superfluous to many users, creating a great gap in cost and services between users and technology. Using the emerging 3D printing technology, my project is to construct a 3D printed robotic hand that can reproduce as many …