Medicine and Health Sciences Commons^™

Fmri Feature Extraction Model For Adhd Classification Using Convolutional Neural Network, Senuri De Silva, Sanuwani Udara Dayarathna, Gangani Ariyarathne, Dulani Meedeniya, Sampath Jayarathna

Computer Science Faculty Publications

Biomedical intelligence provides a predictive mechanism for the automatic diagnosis of diseases and disorders. With the advancements of computational biology, neuroimaging techniques have been used extensively in clinical data analysis. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder, with the symptomology of inattention, impulsivity, and hyperactivity, in which early diagnosis is crucial to prevent unwelcome outcomes. This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to …

Combining Cryo-Em Density Map And Residue Contact For Protein Secondary Structure Topologies, Maytha Alshammari, Jing He

Computer Science Faculty Publications

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments and a set of traces of secondary structures in three-dimensional space. In order to enhance accuracy in ranking secondary structure topologies, we explored a method that combines three sources of information: a set …

A Model For Inhalation Of Infectious Aerosol Contaminants In An Aircraft Passenger Cabin, Bert A. Silich

International Journal of Aviation, Aeronautics, and Aerospace

Aerosol contamination of an aircraft cabin by infectious passengers is a concern of passengers, aircrew and the aviation industry. This may be especially important during a pandemic, such as COVID-19, where the full extent of aerosol transmission is not well understood. A statistical method to determine the number of infectious passengers on board along with a mathematical model estimating the contaminant concentration of aerosols in the cabin and the number of inhaled infectious particles by passengers is presented. An example is used to demonstrated how the results can be estimated during normal operations and emergency conditions with malfunctions of the …

“Conservation Agriculture, " Possible Climate Change Adaptation Option In Taita Hills, Kenya, Lilian Motaroki, Gilbert Ouma, Dorcas Kalele

All Peer-Reviewed Publications

The vicious cycle of food insecurity in Kenya and Africa at large is partly attributed to the high reliance on rainfed agriculture, which makes production systems vulnerable to the adverse impacts of climate change and variability. Conservation agriculture (CA) has been disseminated as a climate-smart practice that operates on three main principles to realize the multiple benefits of making crop production systems more resilient to climate change impacts, enhancing food security, and providing environmental services, such as carbon sequestration. As a major source of livelihood in the Taita Hills, agriculture is constrained by climate change owing to its rainfed nature. …

A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo

Theses and Dissertations

Visualization of liver tumors on simulation CT scans is challenging even with contrast-enhancement, due to the sensitivity of the contrast enhancement to the timing of the CT acquisition. Image registration to magnetic resonance imaging (MRI) can be helpful for delineation, but differences in patient position, liver shape and volume, and the lack of anatomical landmarks between the two image sets makes the task difficult. This study develops a U-Net based neural network for automated liver and tumor segmentation for purposes of radiotherapy treatment planning. Non-contrast simulation based abdominal CT axial scans of 52 patients with primary liver tumors were utilized. …

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) …

Live Cell Biomass Tracking For Basic, Translational, And Clinical Research, Graeme Murray

Theses and Dissertations

Single cell mass is tightly regulated throughout generations and the cell cycle, making it an important marker of cell health. Abnormal changes in cell size can be the first indication of dysfunction in response to environmental stimuli such as cytotoxic drugs. Described here is the further development of high-speed live cell interferometry (HSLCI) to concurrently measure the changes in single cell mass of thousands of cells over time. Critically, the high-throughput nature of HSLCI provides realistic pictures of tumor heterogeneity. This throughput enabled HSLCI to correctly predict in vivo carboplatin sensitivity of three triple negative breast cancer patient derived xenografts, …

A Novel Augmented Deep Transfer Learning For Classification Of Covid-19 And Other Thoracic Diseases From X-Rays, Fouzia Atlaf, Syed M. S. Islam, Naeem K. Janjua

Research outputs 2014 to 2021

Deep learning has provided numerous breakthroughs in natural imaging tasks. However, its successful application to medical images is severely handicapped with the limited amount of annotated training data. Transfer learning is commonly adopted for the medical imaging tasks. However, a large covariant shift between the source domain of natural images and target domain of medical images results in poor transfer learning. Moreover, scarcity of annotated data for the medical imaging tasks causes further problems for effective transfer learning. To address these problems, we develop an augmented ensemble transfer learning technique that leads to significant performance gain over the conventional transfer …

Estimation Of The Healthcare Waste Generation During Covid-19 Pandemic In Bangladesh, Tamal Chowdhury, Hemal Chowdhury, Md Salman Rahman, Nazia Hossain, Ashfaq Ahmed, Sadiq M. Sait

School of Mathematical & Statistical Sciences Faculty Publications

COVID-19 pandemic-borne wastes imposed a severe threat to human lives as well as the total environment. Improper handling of these wastes increases the possibility of future transmission. Therefore, immediate actions are required from both local and international authorities to mitigate the amount of waste generation and ensure proper disposal of these wastes, especially for low-income and developing countries where solid waste management is challenging. In this study, an attempt is made to estimate healthcare waste generated during the COVID-19 pandemic in Bangladesh. This study includes infected, ICU, deceased, isolated and quarantined patients as the primary sources of medical waste. Results …

Food Contact Surfaces: Challenges, Legislation And Solutions, Shubham Sharma, Amit Jaiswal, Brendan Duffy, Swarna Jaiswal

Articles

Food contact surfaces (FCSs) include all surfaces that may come in contact with the food during production, processing, and packaging. Food processing industries encounter several challenges due to its microbial interaction with the FCSs, such as cross-contamination of pathogenic microorganisms or allergens in food, formation of biofilm, biodeterioration of food contact surface leads to food with reduced shelf-life and quality. A legal EU framework provides the fundamental postulates for the safety and inertness of all Food Contact Materials (FCMs). Legislations have an important role in providing regulatory guidance on the quality assurance systems and verifying their implementation as a means …

Data-Fusion For Epidemiological Analysis Of Covid-19 Variants In Uae, Anoud Bani-Hani, Anaïs Lavorel, Newel Bessadet

All Works

Since December 2019, a new pandemic has appeared causing a considerable negative global impact. The SARS-CoV-2 first emerged from China and transformed to a global pandemic within a short time. The virus was further observed to be spreading rapidly and mutating at a fast pace, with over 5,775 distinct variations of the virus observed globally (at the time of submitting this paper). Extensive research has been ongoing worldwide in order to get a better understanding of its behaviour, influence and more importantly, ways for reducing its impact. Data analytics has been playing a pivotal role in this research to obtain …

Adaptation Of The Medical Ethics Teaching Questionnaire For The Use Of Taiwanese Medical Students: A Developmental Study, Lee Jing Ning

Student Works (2020-2029)

Medical ethics is among one of the most important competencies in medical education and formal physicians' training. In the past decades, medical ethics education has become a priority within medical education institutions worldwide. In Taiwan, medical ethics was included in the undergraduate medical curricula since 1995. However, students� view upon graduation revealed that they were still lacked confidence about beginning their residency program due to limited understanding of ethical values. Taiwan, as a country with unique cultural belief in the traditional Confucian principles that emphasizes the virtue of �filial piety� and family cohesion in medical decision-making is lacking Taiwanese studies …

Early Detection Of Lung Cancer - A Challenge, Fatma Taher, Neema Prakash, Ashraf Alzaabi

All Works

Lung cancer or lung carcinoma, is a common and serious type of cancer caused by rapid cell growth in tissues of the lung. Lung cancer detection at its earlier stage is very difficult because of the structure of the cell alignment which makes it very challenging. Computed tomography (CT) scan is used to detect the presence of cancer and its spread. Visual analysis of CT scan can lead to late treatment of cancer; therefore, different steps of image processing can be used to solve this issue. A comprehensive framework is used for the classification of pulmonary nodules by combining appearance …

Active Learning Strategy For Covid-19 Annotated Dataset, Amril Nazir, Ricky Maulana Fajri

All Works

The efficient diagnosis of COVID-19 plays a key role in preventing its spread. Recently, many artificial intelligence techniques, such as the deep neural network approach, have been implemented to help efficient diagnosis of COVID-19. However, the accurate performance of deep learning depends on the tuning of many hyperparameters and a large amount of labeled data. This COVID-19 data bottleneck also leads to insufficient human resources for data labeling, which presents a challenging obstacle. In this paper, a novel discriminative batch-mode active learning (DS3) is proposed to allow faster and more effective COVID-19 data annotation. The framework specifically designed to suit …

A Comprehensive Review On Medical Diagnosis Using Machine Learning, Kaustubh Arun Bhavsar, Ahed Abugabah, Jimmy Singla, Ahmad Ali Alzubi, Ali Kashif Bashir, Nikita

All Works

The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis, the fatigue of clinician, or even the high diagnostic complexity in limited time can lead to diagnostic errors. Diagnostic errors have adverse effects on the treatment of a patient. Unnecessary treatments increase the medical bills and deteriorate the health of a patient. Such diagnostic errors that harm the patient in various ways could be minimized using machine learning. Machine learning algorithms could be used to diagnose various diseases with high accuracy. The use of machine …

Solutions For Fermi Questions, January 2022: Question 1: Snow Volume; Question 2: Longbow Arrow Velocity, Larry Weinstein

Physics Faculty Publications

No abstract provided.

Fecal Sample Collection Methods And Time Of Day Impact Microbiome Composition And Short Chain Fatty Acid Concentrations, Jacquelyn Jones, Stacey N. Reinke, Alishum Ali, Debra J. Palmer, Claus T. Christophersen

Research outputs 2014 to 2021

Associations between the human gut microbiome and health outcomes continues to be of great interest, although fecal sample collection methods which impact microbiome studies are sometimes neglected. Here, we expand on previous work in sample optimization, to promote high quality microbiome data. To compare fecal sample collection methods, amplicons from the bacterial 16S rRNA gene (V4) and fungal (ITS2) region, as well as short chain fatty acid (SCFA) concentrations were determined in fecal material over three timepoints. We demonstrated that spot sampling of stool results in variable detection of some microbial members, and inconsistent levels of SCFA; therefore, sample homogenization …

Gene Selection For Cancer Classification: A New Hybrid Filter-C5.0 Approach For Breast Cancer Risk Prediction, Mohammed Hamim, Ismail El Moudden, Hicham Moutachaouik, Mustapha Hain

Department of Medicine Faculty Publications

Despite the significant progress made in data mining technologies in recent years, breast cancer risk prediction and diagnosis at an early stage using DNA microarray technology still a real challenging task. This challenge comes especially from the high-dimensionality in gene expression data, i.e., an enormous number of genes versus a few tens of subjects (samples). To overcome this problem of data imbalance, a gene selection phase becomes a crucial step for gene expression data analysis. This study proposes a new Decision Tree model-based attributes (genes) selection strategy, which incorporates two stages: fisher-score-based filter technique and the gene selection ability of …

Association Between Life Course Social Determinants Of Health And Metabolic Syndrome Among Female Secondary School Teachers In Johor, Mohammad Fadzly Marzuki

Student Works (2020-2029)

Metabolic syndrome, a cluster of multiple risk factors, is known to increase the risk of cardiovascular diseases, diabetes, and certain cancers. Poor health behaviours such as poor dietary intake and physical activities are known risk factors of metabolic syndrome. However, very little is known if the social determinants of health throughout the life�course are associated with metabolic syndrome. The study aimed to explore the association between life-course social determinants of health and metabolic syndrome. The cross-sectional study involved female secondary school teachers living in the state of Johor, Malaysia. The study used available data from the Clustering of Lifestyle risk …

A Hybrid Gene Selection Strategy Based On Fisher And Ant Colony Optimization Algorithm For Breast Cancer Classification, Mohammed Hamim, Ismail El Moudden, Mohan D. Pant, Hicham Moutachaouik, Mustapha Hain

EVMS School of Health Professions Faculty Publications

Breast cancer poses the greatest threat to human life and especially to women's life. Despite the progress made in data mining technology in recent years, the ability to predict and diagnose such fatal diseases based on gene expression data still reveals a limited prediction performance, which may not be surprising since most of the genes in expression data are believed to be irrelevant or redundant. The dimensionality reduction process may be considered as a crucial step to analyze gene expression data, as it can reduce the high dimensionality of the breast cancer datasets, which may result into a better prediction …

Harnessing Acoustic Streaming For Bioanalysis In Microfluidics, Xiaojun Li

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the past few decades, microfluidic technology has been developed rapidly in both fabrication methods and multifunctionality integrations, making it a powerful tool for a wider variety of biological applications. The device fabrication method has expanded from conventional polymer-based micro devices to 3D-printed micro devices, and allows multiple functions such as electric, optic, magnetic and acoustic to be integrated on a single platform. This dissertation focuses on method development of acoustic streaming-based microfluidics in bioanalysis such as immunoassay, enzyme kinetics and DNA fragmentation analysis. In this dissertation, a micromixer was developed based on acoustic streaming generated from sharp-edge structure vibration …

Association Of Incident Cancer To Low-Value Care And Healthcare Cost Burden Among Elderly Medicare Beneficiaries, Chibuzo Iloabuchi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In the United States (US), 25% of healthcare spending is considered wasteful because it is spent reimbursing low-value care. Low-value care is the utilization of healthcare services, medical tests, and procedures that have unclear or no clinical benefit to patients but still exposes them to risk. World-wide, low-value care imposes a significant economic burden on patients, payers, governments, and society. Cancer care among older adults > 65 years is one of the biggest drivers of healthcare expenditure in the US and accounts for nearly 40% of all spending, and low-value care among cancer patients is prevalent and contributes to the financial …

Bypassing The Blood-Brain Barrier: A Physical And Pharmacological Approach For The Treatment Of Metastatic Brain Tumors, Samuel A. Sprowls

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation (a) provided an in depth literature review of methods to disrupt the BBB/BTB and improve therapeutic distribution to brain tumors, (b) evaluated the use of azacitidine as a single agent therapy for the treatment of brain metastasis of breast cancer and a potential molecular mechanism by which brain tropic cells are sensitized to hypomethylating agents, (c) determined the impact cannabidiol has on P-glycoprotein mediated efflux at the blood-brain barrier and its potential for use as a single agent treatment for metastatic brain tumors, (d) developed a preclinical radiation therapy protocol for use in small animals and in vitro …

Grouping Algorithms For Informative Array Testing In Disease Surveillance, David Sokolov

Graduate Theses, Dissertations, and Problem Reports (ETD)

In order to maintain normal operations and prevent unnecessary morbidity and mortality during times of disease outbreak, institutions find a need to conduct frequent and widespread testing of their constituents, often under significantly limited testing resource constraints. Faced with the challenge of how best to allo- cate these limited resources to maximum effect, institutions are increasingly turning to group (or “pooled”) testing, which involves testing strategically-chosen groups of patient samples rather than individual samples, producing significant testing resource savings under certain regimes of disease prevalence. While group test- ing can be conducted without any a priori knowledge of individual disease …

Rapid Transition Of A Technical Course From Face-To-Face To Online, Swapna Gottipatti, Venky Shankaraman

Research Collection School Of Computing and Information Systems

Just like most universities around the world, the senior management at Singapore Management University decided to move all courses to a virtual, online, synchronous mode, giving instructors a very short notice period—one week—to make this transition. In this paper, we describe the challenges, practical solutions adopted, and the lessons learnt in rapidly transitioning a face-to-face Master’s degree course in Text Analytics and Applications into a virtual, online, course format that could deliver a quality learning experience.

Dach1 Mutation Frequency In Endometrial Cancer Is Associated With High Tumor Mutation Burden, Mckayla J. Riggs, Nan Lin, Chi Wang, Dava W. Piecoro, Rachel W. Miller, Oliver A. Hampton, Mahadev Rao, Frederick R. Ueland, Jill M. Kolesar

Obstetrics and Gynecology Faculty Publications

OBJECTIVE: DACH1 is a transcriptional repressor and tumor suppressor gene frequently mutated in melanoma, bladder, and prostate cancer. Loss of DACH1 expression is associated with poor prognostic features and reduced overall survival in uterine cancer. In this study, we utilized the Oncology Research Information Exchange Network (ORIEN) Avatar database to determine the frequency of DACH1 mutations in patients with endometrial cancer in our Kentucky population.

METHODS: We obtained clinical and genomic data for 65 patients with endometrial cancer from the Markey Cancer Center (MCC). We examined the clinical attributes of the cancers by DACH1 status by comparing whole-exome sequencing (WES), …

Medical Marijuana And Opioids (Memo) Study: Protocol Of A Longitudinal Cohort Study To Examine If Medical Cannabis Reduces Opioid Use Among Adults With Chronic Pain, Chinazo O. Cunningham, Joanna L. Starrels, Chenshu Zhang, Marcus A. Bachhuber, Nancy L. Sohler, Frances R. Levin, Haruka Minami, Deepika E. Slawek, Julia H. Arnsten

School of Medicine Faculty Publications

Introduction In the USA, opioid analgesic use and overdoses have increased dramatically. One rapidly expanding strategy to manage chronic pain in the context of this epidemic is medical cannabis. Cannabis has analgesic effects, but it also has potential adverse effects. Further, its impact on opioid analgesic use is not well studied. Managing pain in people living with HIV is particularly challenging, given the high prevalence of opioid analgesic and cannabis use. This study's overarching goal is to understand how medical cannabis use affects opioid analgesic use, with attention to Δ9-tetrahydrocannabinol and cannabidiol content, HIV outcomes and adverse events. Methods and …

Quantifying Anticancer Drug Doxorubicin Binding To Dna Using Optical Tweezers, Zachary Ells

Honors Program Theses and Projects

Doxorubicin is a successful anticancer drug approved for use in the 1970s and is considered to be one of the most effective cancer treatment methods today. Although Doxorubicin has positive survival statistics it has very negative side effects in many cases. Bleeding from the soles of the palms and feet, along with excruciating pain is often exhibited through the administration of this drug. Based on the preliminary findings utilizing optical tweezers we anticipate that this study will provide critical information about the drug binding mechanism. Single molecule biophysics techniques have provided useful insight into the DNA-binding mechanisms of small molecules. …

Core Commitments For Field Trials Of Gene Drive Organisms, Kanya C. Long, Luke Alphey, George J. Annas, Cinnamon S. Bloss, Karl J. Campbell, Jackson Champer, Chun-Hong Chen, Amit Choudhary, George M. Church, James P. Collins, Kimberly L. Cooper, Jason A. Delborne, Owain R. Edwards, Claudia I. Emerson, Kevin Esvelt, Sam Weiss Evans, Robert M. Friedman, Valentino M. Gantz, Fred Gould, Sarah Hartley, Elizabeth Heitman, Janet Hemingway, Hirotaka Kanuka, Jennifer Kuzma, James V. Lavery, Yoosook Lee, Marce Lorenzen, Jeantine E. Lunshof, John M. Marshall, Philipp W. Messer, Craig Montell, Kenneth A. Oye, Megan J. Palmer, Philippos Aris Papathanos, Prasad N. Paradkar, Antoinette J. Piaggio, Jason L. Rasgon, Gordana Rašić, Larisa Rudenko, J. Royden Saah, Maxwell J. Scott, Jolene T. Sutton, Adam E, Vorsino, Omar S. Akbari

United States Department of Agriculture Wildlife Services: Staff Publications

We must ensure that trials are scientifically, politically, and socially robust, publicly accountable, and widely transparent.

Gene drive organisms (GDOs), whose genomes have been genetically engineered to spread a desired allele through a population, have the potential to transform the way societies address a wide range of daunting public health and environmental challenges. The development, testing, and release of GDOs, however, are complex and often controversial. A key challenge is to clarify the appropriate roles of developers and others actively engaged in work with GDOs in decision-making processes, and, in particular, how to establish partnerships with relevant authorities and other …

Applied Molecular Dynamics: From Targeting Viral Helicases, To Understanding The Interactions Of Cucurbituril Complexes In Ionic Solutions, Bryan Raubenolt

LSU New Orleans Theses and Dissertations

Molecular Dynamics simulations are a highly useful tool in helping understand the fundamental interactions present in a variety of chemical systems. The work discussed here illustrates it’s use in determining the conformational dynamics of the Zika and SARS-Cov-2 helicase in a physiological environment, largely in an effort to discover inhibitors capable of rendering the protein inert. Additionally, we show how it can be used to understand paradoxical trends in the anion-induced precipitation of Cucurbituril cavitands.

Viral helicases are motor proteins tasked with unwinding the viral dsRNA, a crucial step in preparing the strand to be translatable by host cells. By …