Investigative Techniques Commons^™

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 …

A Quality Improvement Project To Improve Management Of Urinary Tract Infections In A System Of Pediatric Urgent Care Centers, Benjamin Klick, Tammy Speerhas, Jessica Parrott, Jeffrey Bobrowitz, Anne Mcevoy, Debra Conrad, Theresa Guins

Nursing Faculty Publications

Background and objective: Urinary tract infections (UTIs) are a common problem in pediatric urgent care medicine. There are multiple quality improvement (QI) projects related to the management of UTIs documented in the pediatric literature. We developed a project to decrease the prescribing of ultimately unneeded antibiotics for possible UTIs in a pediatric urgent care setting. A similar project has not been described in the pediatric literature.

Methods: We first reviewed the charts of patients presenting to a system of pediatric urgent care centers with a possible UTI over a 2-year period. We then launched a QI project with three plan, …

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 …

Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …

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 …

Disordered Eating, Food Insecurity, And Weight Status Among Transgender And Gender Nonbinary Youth And Young Adults: A Cross-Sectional Study Using A Nutrition Screening Protocol, Whitney R. Linsenmeyer, Ian M. Katz, Jaime L. Reed, Andrea M. Giedinghagen, Christopher B. Lewis, Sarah K. Garwood

Psychology Faculty Publications

Purpose: The purpose of this study was to describe the prevalence of and relationships among disordered eating, food insecurity, and weight status among transgender and gender nonbinary youth and young adults.

Methods: This cross-sectional study involved a screening protocol to assess disordered eating and food insecurity risk from September to December of 2019 at a gender clinic using five validated measures: (1) previous eating disorder diagnosis (yes/no); (2) Sick, Control, One Stone, Fat, Food Questionnaire (SCOFF); (3) Adolescent Binge Eating Disorder Questionnaire (ADO-BED); (4) Nine-Item Avoidant/Restrictive Food Intake Disorder Screen (NIAS); and (5) Hunger Vital Sign. Age, assigned sex at …

Tri-Molybdenum Phosphide (Mo3P) And Multi-Walled Carbon Nanotube Junctions For Volatile Organic Compounds (Vocs) Detection, Baleeswaraiah Muchharla, Praveen Malali, Brenna Daniel, Alireza Kondori, Mohammad Asadi, Wei Cao, Hani E. Elsayed-Ali, Mickaël Castro, Mehran Elahi, Adetayo Adedeji, Kishor Kumar Sadasivuni, Muni Raj Mauya, Kapil Kumar, Abdennaceur Karoui, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Detection and analysis of volatile organic compounds’ (VOCs) biomarkers lead to improvement in healthcare diagnosis and other applications such as chemical threat detection and food quality control. Here, we report on tri-molybdenum phosphide (Mo₃P) and multi- walled carbon nanotube (MWCNT) junction-based vapor quantum resistive sensors (vQRSs), which exhibit more than one order of magni- tude higher sensitivity and superior selectivity for biomarkers in comparison to pristine MWCNT junctions based vQRSs. Transmission electron microscope/scanning tunneling electron microscope with energy dispersive x-ray spectroscopy, x-ray diffraction, and x-ray photo- electron spectroscopy studies reveal the crystallinity and the presence of Mo and …

Adaptive Physics-Based Non-Rigid Registration For Immersive Image-Guided Neuronavigation Systems, Fotis Drakopoulos, Christos Tsolakis, Angelos Angelopoulos, Yixun Liu, Chengjun Yao, Kyriaki Rafailia Kavazidi, Nikolaos Foroglou, Andrey Fedorov, Sarah Frisken, Ron Kikinis, Alexandra Golby, Nikos Chrisochoides

Computer Science Faculty Publications

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A …

Single-Molecule Analysis Of Subtelomeres And Telomeres In Alternative Lengthening Of Telomeres (Alt) Cells, Heba Z. Abid, Jennifer Mccaffrey, Kaitlin Raseley, Eleanor Young, Katy Lassahn, Dharma Varapula, Harold Riethman, Ming Xiao

Medical Diagnostics & Translational Sciences Faculty Publications

BACKGROUND: Telomeric DNA is typically comprised of G-rich tandem repeat motifs and maintained by telomerase (Greider CW, Blackburn EH; Cell 51:887-898; 1987). In eukaryotes lacking telomerase, a variety of DNA repair and DNA recombination based pathways for telomere maintenance have evolved in organisms normally dependent upon telomerase for telomere elongation (Webb CJ, Wu Y, Zakian VA; Cold Spring Harb Perspect Biol 5:a012666; 2013); collectively called Alternative Lengthening of Telomeres (ALT) pathways. By measuring (TTAGGG) n tract lengths from the same large DNA molecules that were optically mapped, we simultaneously analyzed telomere length dynamics and subtelomere-linked structural changes at a large …

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 …

Visual Estimates Of Blood Loss By Medical Laypeople: Effects Of Blood Loss Volume, Victim Gender, And Perspective, Rachel Phillips, Marc Friberg, Mattias Lantz Cronqvist, Carl-Oscar Jonson, Erik Prytz

Psychology Faculty Publications

A severe hemorrhage can result in death within minutes, before professional first responders have time to arrive. Thus, intervention by bystanders, who may lack medical training, may be necessary to save a victim's life in situations with bleeding injuries. Proper intervention requires that bystanders accurately assess the severity of the injury and respond appropriately. As many bystanders lack tools and training, they are limited in terms of the information they can use in their evaluative process. In hemorrhage situations, visible blood loss may serve as a dominant cue to action. Therefore, understanding how medically untrained bystanders (i.e., laypeople) perceive hemorrhage …

Can Nanotechnology Be The Leading Method In Detecting And Treating Cerebral Tumors?, Daniel D. Singh, Zuri Jules-Culver

OUR Journal: ODU Undergraduate Research Journal

Nanotechnology refers to the manipulation or design of materials and structures with desired features in the 1nm–1000 nm size range. The blood brain barrier (BBB) is a major obstacle that drugs must overcome in order to reach tumor cells. The role of this barrier is to transport essential nutrients while protecting and regulating the internal environment. Nanoparticles have been shown to transport drugs through this barrier and accumulate in tumor cells. This is significant since nanoparticles are drug carriers allowing chemotherapeutic drugs to accumulate in target areas (Sun et al., 2017). This is possible because they are able to be …

Use Of An Optical Scanning Device To Monitor The Progress Of Noninvasive Treatments For Chest Wall Deformity: A Pilot Study, Robert E. Kelly Jr., Robert J. Obermeyer, Ann Kuhn, Frazier W. Frantz, Mohammad F. Obeid, Nahom Kidane, Frederic D. Mckenzie

Computational Modeling & Simulation Engineering Faculty Publications

Background: The nonsurgical treatment of chest wall deformity by a vacuum bell or external brace is gradual, with correction taking place over months. Monitoring the progress of nonsurgical treatment of chest wall deformity has relied on the ancient methods of measuring the depth of the excavatum and the protrusion of the carinatum. Patients, who are often adolescent, may become discouraged and abandon treatment. Methods: Optical scanning was utilized before and after the intervention to assess the effectiveness of treatment. The device measured the change in chest shape at each visit. In this pilot study, patients were included if they were …

Bioelectrics In Basic Science And Medicine: Impact Of Electric Fields On Cellular Structures And Functions, Stephen J. Beebe

Bioelectrics Publications

Bioelectrics is a new interdisciplinary field that investigates electric field effects on cell membranes and other cellular components. It incorporates four main technologies, including electroporation, nanosecond pulsed electric fields, picosecond pulsed electric fields and cold plasmas. The parent technology in Bioelectrics is electroporation, which uses milli- and/or micro-second electric pulses to permeabilize cells and tissues, for delivery of membrane impermeable molecules. It is now being used for electro-gene delivery, with vascular endothelial growth factor, for revascularization in wound healing and cardiovascular and peripheral vascular disease. Plasmids expressing IL-12 are being delivered for immune system activation in melanoma treatment, now in …

Facilitation Of Electroporative Drug Uptake And Cell Killing By Electrosensitization, Olga N. Pakhomova, Betsy W. Gregory, Andrei G. Pakhomov

Bioelectrics Publications

Cell permeabilization by electric pulses (EP), or electroporation, is widely used for intracellular delivery of drugs and plasmids, as well as for tumour and tissue ablation. We found that cells pre-treated with 100-mus EP develop delayed hypersensitivity to subsequent EP applications. Sensitizing B16 and CHO cells by splitting a single train of eight 100-mus EP into two trains of four EP each (with 5-min. interval) decreased the LD(50) 1.5-2 times. Sensitization profoundly enhanced the electroporation-assisted uptake of bleomycin, a cell-impermeable cytotoxic agent accepted for killing tumours by electrochemotherapy. EP exposures that were not lethal per se caused cell death in …

Tpm: Cloud-Based Tele Ptsd Monitor Using Multi-Dimensional Information, Roger Xu, Gang Mei, Guangfan Zhang, Pan Gao, Aaron Pepe, Jiang Li, James D. Westwood (Ed.), Susan W. Westwood (Ed.), Li Felländer-Tsai (Ed.), Randy S. Haluck (Ed.), Richard A. Robb (Ed.), Steven Senger (Ed.), Kirby G. Vosburgh (Ed.)

Electrical & Computer Engineering Faculty Publications

An automated system that can remotely and non-intrusively screen individuals at high risk for Post-Traumatic Stress Disorder (PTSD) and monitor their progress during treatment would be desired by many Veterans Affairs (VAs) as well as other PTSD treatment and research organizations. In this paper, we present an automated, cloud-based Tele-PTSD Monitor (TPM) system based on the fusion of multiple sources of information. The TPM system can be hosted in a cloud environment and accessed through landline or cell phones, or on the Internet through a web portal or mobile application (app).

A Voice-Based Automated System For Ptsd Screening And Monitoring, Roger Xu, Gang Mei, Guangfan Zhang, Pan Gao, Timothy Judkins, Michael Cannizzaro, Jiang Li, James D. Westwood (Ed.), Susan W. Westwood (Ed.), Li Felländer-Tsai (Ed.), Randy S. Haluck (Ed.), Richard A. Robb (Ed.), Steven Senger (Ed.), Kirby G. Vosburgh (Ed.)

Electrical & Computer Engineering Faculty Publications

Comprehensive evaluation of PTSD includes diagnostic interviews, self-report testing, and physiological reactivity measures. It is often difficult and costly to diagnose PTSD due to patient access and the variability in symptoms presented. Additionally, potential patients are often reluctant to seek help due to the stigma associated with the disorder. A voice-based automated system that is able to remotely screen individuals at high risk for PTSD and monitor their symptoms during treatment has the potential to make great strides in alleviating the barriers to cost effective PTSD assessment and progress monitoring. In this paper we present a voice-based automated Tele-PTSD Monitor …

Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)

Electrical & Computer Engineering Faculty Publications

In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …

Automatic Diagnosis For Prostate Cancer Using Run-Length Matrix Method, Xiaoyan Sun, Shao-Hui Chuang, Jiang Li, Frederic Mckenzie, Nico Karssemeijer (Ed.), Maryellen L. Giger (Ed.)

Electrical & Computer Engineering Faculty Publications

Prostate cancer is the most common type of cancer and the second leading cause of cancer death among men in US¹. Quantitative assessment of prostate histology provides potential automatic classification of prostate lesions and prediction of response to therapy. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. In this application, we utilize a texture analysis method based on the run-length matrix for identifying tissue abnormalities in prostate histology. A tissue sample was collected from a radical prostatectomy, H&E fixed, and assessed by a pathologist …

Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)

Electrical & Computer Engineering Faculty Publications

We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …

Applications Of Wavelet Transforms In Biomedical Optoacoustics, Zibiao Wei, Shujun Yang, Amin N. Dharamsi, Barbara Hargrave

Biological Sciences Faculty Publications

We discuss the utility of wavelet transform methods in signal processing in general, and in particular, demonstrate the technique in optoacoustic applications. In several optoacoustic experiments with different samples, we have successfully enhanced the signal to noise ratios. Wavelet transforms optimize resolution by utilizing a tailored, variable time-window in different frequency regions. The technique's great advantage lies in the fact that the wavelet transform adds some redundancy to the original signal, and some desired features can be enhanced in the transformed space. In addition, proper choice of the basis set allows a sparse representation of the signal. Therefore, even when …