Investigative Techniques Commons^™

Identifying Relevant Covariates In Rna-Seq Analysis By Pseudo-Variable Augmentation, Yet Nguyen, Dan Nettleton

Mathematics & Statistics Faculty Publications

RNA-sequencing (RNA-seq) technology allows for the identification of differentially expressed genes, which are genes whose mean transcript abundance levels vary across conditions. In practice, RNA-seq datasets often include covariates that are of primary interest in addition to a set of covariates that are subject to selection. Some of these covariates may be relevant to gene expression levels, while others may be irrelevant. Ignoring relevant covariates or attempting to adjust for the effect of irrelevant covariates can compromise the identification of differentially expressed genes. To address this issue, we propose a variable selection method that uses pseudo-variables to control the expected …

Ai-Assisted Surface-Enhanced Raman Spectroscopy For Cardiovascular Diagnostics: From Plasmonic Materials To Clinical Translation, Anju Joshi, Gymama Slaughter

Center for Bioelectronics Publications

Raman spectroscopy (SERS) has emerged as a powerful analytical technique, offering molecular fingerprint specificity and ultrasensitive detection of cardiac biomarkers. Recent advances in plasmonic nanostructures, surface functionalization strategies, and flexible sensing platforms have significantly improved the analytical performance of SERS-based biosensors. In parallel, the integration of artificial intelligence (AI) and machine learning has enabled robust interpretation of complex spectral datasets, facilitating automated biomarker classification and improved diagnostic accuracy in heterogeneous biological environments. Despite these advances, the field remains fragmented, with limited integration between nanomaterial design, biomarker selection, and data-driven analysis, and persistent challenges related to reproducibility, standardization, and clinical validation. …

Modulation Of Prussian Blue Redox Signaling By Molecular Imprinting For Reagent-Free Electrochemical Detection Of Emtricitabine, Abdellatif Ait Lahcen, Gymama Slaughter

Center for Bioelectronics Publications

Reagent-free electrochemical sensors offer significant benefits for rapid, affordable point-of-care drug testing. In this study, we introduce a novel, reagent-free electrochemical sensor based on a molecularly imprinted polymer (MIP) specifically designed for the selective detection of Emtricitabine (FTC), a common antiretroviral used in HIV therapy. The sensor uses laser-induced graphene (LIG) electrodes, renowned for their high conductivity and porosity, ideal for electrochemical sensing. To enable reagent-free operation, the LIG surface was electrochemically coated with Prussian Blue, serving as a redox-active layer. Next, an MIP-PPy film was electropolymerized onto the Prussian Blue surface in the presence of FTC as a template, …

A Painful Diffuse Rash, Bruce M. Lo, Melanie Shoemaker, Kiersten Potter, Katherine Schaffer

Department of Emergency Medicine Faculty Publications

[Patient presentation]

A 41-year-old male with no past medical history presented with 1 week of ulcers to the left side of his face, followed by several days of a painful rash to the trunk and back after a sexual encounter. The patient denies any fever or previous rash and any illicit drug use. Initial vital signs included a temperature of 97 °F, a heart rate of 89 beats per minute, and blood pressure of 135/79 mm Hg. Physical examination revealed a macular papular rash across his trunk and back (Fig 1) and facial ulcerations with eschar (Fig 2) at the …

Dementia Incidence In Patients With Prurigo Nodularis: An Observational Retrospective Cohort Study, Madison P. Olexson, Ana Ormaza Vera, Chunghwan Ro, Clinton W. Enos

Department Dermatology Faculty Publications

[Introduction] Prurigo nodularis (PN) is a chronic neuroinflammatory dermatosis of unknown etiology characterized by severely pruritic, symmetrically-distributed nodules with a negative impact on quality of life [1]. While some consider PN a primary idiopathic disorder, it often arises as a secondary manifestation of underlying conditions, including atopic dermatitis (AD), chronic kidney disease (CKD), human-immunodeficiency-virus (HIV), and thyroid disorders [2]. Although patients with PN are at higher risk for psychiatric comorbidities including depression, anxiety, and suicidal ideation [3] research which investigates associations between PN and neurodegenerative disorders is limited [4]. Moreover, emerging evidence implicating sustained systemic inflammation, characteristic of psoriasis and …

Brief Pulses Of High-Level Fluid Shear Stress Enhance Metastatic Potential And Rapidly Alter The Metabolism Of Cancer Cells, Amanda N. Pope, Devon L. Moose, Guy O. Hudson, Hank R. Weresh, Marion R. Dykstra, Aabha Y. Joshi, Patrick Breheny, Eric B. Taylor, Michael D. Henry

Department of Biomedical and Translational Sciences Faculty Publications

Circulating tumor cells (CTCs) face challenges to their survival, including mechanical and oxidative stresses that are different from cancer cells in solid primary and metastatic tumors. The impact of adaptations to the fluid microenvironment of the circulation on the outcome of the metastatic cascade is not well understood. Here, we find that cancer cells exposed to brief pulses of high-level fluid shear stress (FSS) exhibit enhanced invasiveness and anchorage-independent proliferation in vitro and enhanced metastatic colonization/tumor formation in vivo. Cancer cells exposed to FSS rapidly alter their metabolism in a manner that promotes survival by providing energy for cytoskeletal remodeling …

Preoperative Patient Sentiment Is Associated With Postoperative Outcomes In Adult Spinal Deformity Surgery, Ross J. Gore, David Mazur-Hart, Mohan K. Sunkara, Aaqib Ali, Qizar Ali, Christopher J. Lynch, Christopher Ames

Center for Secure and Intelligent Critical Systems (CSICS) Publications

Study Design: Prospective observational pilot study of adult spinal deformity surgery patients.

Objective: To determine whether preoperative patient sentiment, quantified using a 21-class valence scale extending the CARP paradigm implemented through an offline Large Language Model, predicts postoperative outcomes.

Summary of Background Data: Predicting adult spinal deformity surgery outcomes remains challenging with traditional clinical and radiographic parameters alone. Although patient psychological factors and expectations significantly influence postoperative satisfaction and quality of life, systematic approaches to capture these factors are underdeveloped. Offline Large Language Models offer scalable, privacy-preserving psychological risk stratification.

Materials and Methods: We prospectively enrolled 18 patients undergoing adult …

Revisiting Nasal Polyp Scoring In Clinical Trials: Interpretive Variability And The Need For Standardization, Leigh J. Sowerby, Babak Pourmomenarabi, Antonino Maniaci, Olivia Ginty, Joseph Khristian Han

Department of Otolaryngology (ENT) Faculty Publications

[Introduction] Borish et al. provided an excellent review highlighting methodological variability among the six pivotal Phase III trials [1]. One critical yet overlooked issue is the inconsistent application of the endoscopic nasal polyp score (NPS), a primary outcome measure in all trials.

Microarray Analysis Of Human Abdominal Aortic Aneurysm With Emphasis On Cardiovascular Genes Revealed Differentially Expressed Genes, Song Lu, Li Ping Li, John V. White, Xiaoying Zhang, Ifeyinwa Nwaneshiudu, Adaobi Nwaneshiudu, Nectaria Ntaoula, John Gaughan, Dimitri S. Monos, Wan-Lu Lin, Charalambos C. Solomides, Emilia L. Oleszak, Chris D. Platsoucas

Biological Sciences Faculty Publications

Background/Aim: We examined gene expression profiles in abdominal aortic aneurysm (AAA) lesions vs. normal aortas by cDNA microarray and real-time quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR).

Materials and Methods: Phosphorus (32P)-labeled cDNA from AAA specimens (mean AAA size 6.65 cm) and normal aortas were hybridized with a 588-gene microarray primarily of the cardiovascular system. The results were validated by qRT-PCR.

Results: A total of 35 out of the 588 genes were differentially expressed, with either log2 ratio of AAAs/controls ≥1 (upregulated; 20 genes) or ≤−1 (downregulated; 15 genes) in AAA lesions vs. normal aorta, and 25 of these were significantly …

Near Real-Time Adaptive Isotropic And Anisotropic Image-To-Mesh Conversion For Cerebral Aneurysm Simulations, Kevin Garner, Chander Sadasivan, Nikos Chrisochoides

Computer Science Faculty Publications

This paper presents two performance optimization techniques for a mesh adaptation method that is designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. This method is integrated into a pipeline with an image-to-mesh conversion tool to generate adaptive anisotropic meshes from segmented medical images. The pipeline is shown to satisfy quality, fidelity, smoothness, and robustness requirements while providing near real-time performance for medical image-to-mesh conversion. Tested with two brain aneurysm cases and utilizing up to 96 CPU cores within a single, multicore node on Purdue University’s Anvil supercomputer, the parallel adaptive anisotropic meshing method …

Adaptive Self-Attention For Enhanced Segmentation Of Adult Gliomas In Multi-Modal Mri, Evan P. Savaria, Jiangwen Sun

Computer Science Faculty Publications

Every year there are an estimated 80,000–90,000 new glioma cases, highlighting the need for reliable imaging-based decision support. Although deep learning has improved tumor sub-region segmentation, many state-of-the-art models fail to fully capture complementary information across T1, T1Gd, T2, and FLAIR MRI modalities and often operate as “black boxes,” limiting physician trust when precise delineation is critical for surgical planning, radiation targeting, and treatment monitoring. To address these limitations, we propose AIMS, an Adaptive Integrated Multi-Modal Segmentation framework that maintains modality-specific feature streams and employs adaptive self-attention within a hierarchical CNN-Transformer architecture to prioritize and fuse multi-modal MRI features. We …

Hungarian Validation Of The Pelvic Floor Distress Inventory - 20 (Pfdi-20) Questionnaire And The Pelvic Floor Impact Questionnaire - 7 (Pfiq - 7), Barbara Kozma, Bence Kozma, Peter Takacs, Dávid Rátonyi, Nelli Farkas, Attila G. Sipos, Balint Farkas

Department of Obstetrics & Gynecology Faculty Publications

Introduction and Hypotheses

Pelvic floor disorders (PFDs) affect women's quality of life through physical, psychological, and social domains. The Pelvic Floor Distress Inventory-20 (PFDI-20) and the Pelvic Floor Impact Questionnaire-7 (PFIQ-7) are validated tools for assessing symptom severity and quality of life impact. The current study aim to investigate the reliability and validity of the Hungarian versions of these questionnaires in women with PFD symptoms.

Methods

This validation study was carried out at the University of Debrecen among women with clinically confirmed pelvic floor disorders. The PFDI-20 and PFIQ-7 questionnaires were translated into Hungarian using independent native English speaker in …

Baseline Lymphopenia Predicts Survival In Ici-Naïve Solid Tumor Patients Receiving Immune Checkpoint Inhibitors: A Propensity-Matched Real-World Pan-Cancer Analysis, Ahmed Ismail, Nina Balanchivadze, George R. Simon, Yanis Boumber

Department of Medicine Faculty Publications

Background: Baseline lymphopenia is common among advanced solid tumors and may influence the efficacy/safety of immune checkpoint inhibitors (ICIs), but large real-world evidence is limited. We evaluated the association between baseline absolute lymphocyte count (ALC) and clinical outcomes in adults with solid tumors treated with ICIs in routine practice. Methods: We performed a retrospective cohort study using TriNetX. Adults with solid tumors who received pembrolizumab, nivolumab, or atezolizumab (ICI-Naïve) between January 2015 and June 2026 were included. Baseline ALC was measured within 30 days before first treatment and was classified as lymphopenic (ALC < 1.5 × 10⁹/L) or non-lymphopenic (ALC ≥ 1.5 × 10⁹/L). Propensity score matching (1:1) yielded 5249 patients per group. The index date was the first immunotherapy date, and outcomes were assessed at 6, 12, 24, 36 months, and 5 years. The primary outcome was 24-month overall survival (OS); secondary outcomes were OS at 6 and 12 months and 6-month risks of healthcare utilization, immune-related adverse events (irAEs), and serious infections; and exploratory outcomes included OS at 36 months and 5 years. All outcomes were analyzed using Kaplan–Meier analysis, Cox proportional hazards models, and risk ratios. Subgroup analysis included OS stratified by solid tumor subtypes and prior lines of therapy. Results: After matching, patients with baseline lymphopenia …

When Unilateral Leg Swelling Is Not Deep Vein Thrombosis: A Case Of Disseminated Kaposi Sarcoma Revealing Advanced Human Immunodeficiency Virus, Ahmed Ismail, Zachary Wilson, Thomas Currow, Michael Dileonardo, Carsten Kirby

Department of Medicine Faculty Publications

Kaposi sarcoma (KS) is an acquired immunodeficiency syndrome (AIDS)-defining malignancy that can involve the skin, lymph nodes, and visceral organs in patients with advanced human immunodeficiency virus (HIV). We report the case of a 35-year-old man with no known prior medical history who presented to the charity care clinic complaining of recurrent thrush and two weeks of progressive right lower extremity swelling. His physical examination revealed painful, pruritic violaceous papules and plaques over the proximal right thigh that had been present for one week. He was referred to the emergency department (ED) for further workup. Venous duplex ultrasonography was negative …

Redo Tavr With Asymmetric Coronary Risk: Interpreting Borderline Ct Findings, Connor J. Mckechnie, Nicolas J. Valle, Omar A. Saleh, Matthew R. Summers, Deepak R. Talreja

Department of Medicine Faculty Publications

Image(s)

Computed tomography (CT) and computational modeling (DASI) in redo transcatheter aortic valve replacement (TAVR) planning.

Case Summary

A 77-year-old woman presented with severe symptomatic aortic stenosis due to degeneration of a prior transcatheter valve. CT demonstrated leaflet calcification with borderline left-sided valve-to-coronary distance (3.27 mm). Geometric assessment suggested low right coronary obstruction risk, but higher left main risk. Computational modeling demonstrated adequate leaflet-coronary clearance (distance from displaced leaflet cusp to coronary ostium normalized to coronary diameter >0.7). Redo TAVR with a 26-mm Evolut FX was performed without leaflet modification and no coronary obstruction.

Take-Home Message

Borderline CT findings in …

Motion Artifacts Removal From Measured Arterial Pulse Signals At Rest: A Generalized Sdof-Model-Based Time-Frequency Method, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Motion artifacts (MA) are a key factor affecting the accuracy of a measured arterial pulse signal at rest. This paper presents a generalized time–frequency method for MA removal that is built upon a single-degree-of-freedom (SDOF) model of MA, where MA is manifested as time-varying system parameters (TVSPs) of the SDOF system for the tissue–contact-sensor (TCS) stack between an artery and a sensor. This model distinguishes the effects of MA and respiration on the instant parameters of harmonics in a measured pulse signal. Accordingly, a generalized SDOF-model-based time–frequency (SDOF-TF) method is developed to obtain the instant parameters of each harmonic in …

Motion Artifacts (Ma) At-Rest In Measured Arterial Pulse Signals: Time-Varying Amplitude In Each Harmonic And Non-Flat Harmonic-Ma Coupled Baseline, Md Mahfuzur Rahman, Mamun Hasan, Zhili Hao

Mechanical & Aerospace Engineering Faculty Publications

Motion artifacts (MA) cause great variability in a measured arterial pulse signal, and treatment of MA solely as a baseline drift (BD) fails to eliminate its effect on the measured signal. This paper presents a study on the effect of MA at rest (< 0.7 Hz) on measured arterial pulse signals using a microfluidic-based tactile sensor. By taking full account of the dynamic behavior of the transmission path from the true pulse signal in an artery to a measured pulse signal at the sensor, the tissue-contact-sensor (TCS) stack, an analytical model of MA in a measured pulse signal is developed. In this model, the TCS stack is treated as a 1DOF system for its dynamic behavior; MA is quantified as the displacement (i.e., BD) and time-varying system parameters (TVSP) of the TCS stack. The mathematical expression of MA in a measured pulse signal reveals that while BD remains as low-frequency additive noise, TVSP causes time-varying harmonics in a measured pulse signal. Further time-frequency analysis (TFA) of measured pulse signals validates the existence of TVSP and, for the first time, reveals its effect on a measured pulse signal: time-varying amplitude in each harmonic and non-flat harmonic-MA-coupled baseline.

Prevalence Of Electrocardiographic Changes And Risk Factors For Qtc Prolongation Among Steady State Sickle Cell Disease Patients: Cooperative Study Of Sickle Cell Disease, Mohammed B. Nawaiseh, Rund R. Haddadin, Yara B. Nawaiseh, Mohammad Z. Salameh, Abdallah A. Shurman, Osama Abu-Shawer, Asma I. Aljesrawi, Ibrahim A. Abuelbeh, Allaa Roto, Hadil Zureigat, Lana Mango, Munir Q. Zaqqa, Hanna K. Al-Makhamreh, Nakhleh Abu-Yaghi

Department of Medicine Faculty Publications

Objectives: Sickle cell disease (SCD) is associated with several cardiovascular adverse events. Corrected QT (QTc) interval prolongation is one of the potential life-threatening complications that predispose patients to sudden cardiac death. This study aims to assess the prevalence of electrocardiogram (ECG) changes and to investigate risk factors associated with increased propensity of QTc prolongation. Methods: This study utilized data from the Cooperative Study of Sickle Cell Disease Cardiac Ancillary Study. QT intervals were corrected using the Bazett formula, and prolongation was defined using sex-specific thresholds. The study population included African American patients with steady-state SCD across four clinical centers located …

Cultures For Acid-Fast Bacilli: Are We Being Good Stewards?, Jennifer Hanrahan, Julie D. Sill, Patricia Ver Schneider, Jessica F. Copeland, Elsie Frimpongmaa Amoako-Kissi, Ogochukwu O. Ilobi, Angela J. Toepp

Department of Medicine Faculty Publications

Objective: To describe the use of cultures for acid-fast bacilli (AFB) and situations in which AFB cultures are unlikely to be of clinical benefit.

Design: Retrospective descriptive study of AFB cultures submitted to Sentara Health microbiology laboratory from December 1, 2021, to December 1, 2023. Data were collected from the electronic medical record and included patient demographics, the service line that ordered the culture, specimen source, and culture results.

Setting: Sentara Healthcare System.

Patients: All patients who had specimens submitted to the microbiology laboratory during the study period were included.

Results: A total of 13,944 AFB cultures from 8,243 …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

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 …

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

Ellmer School of 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, …

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 …

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 …

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 …

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 …

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 …

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

School of Medical Diagnostics & Translational Sciences 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 …