Physical Sciences and Mathematics Commons^™

Computational Study Of Binding Of Oseltamivir To Neuraminidase Mutants Of Influenza A Virus, Muhammad Arba, Sri Wahyuli, Setyanto Tri Wahyudi, Amir Karton, Chun Wu

Faculty Scholarship for the College of Science & Mathematics

Oseltamivir (OTV), which targets the neuraminidase (NA) of Influenza A virus (IAV), has been reported to develop resistance. Here, we performed a computational study on the binding modes of OTV in the wild-type and popular mutants of IAV NA (E119A, E119D, E119G, H274Y, I117T, I117V, I117V-E119A, K150N, N294S, R292K, V116A, and Y252H). The Arg118, Glu119, Asp151, Arg152, Glu276, Arg292, and Arg371 were identified as crucial interacting residues with the drug. The energy decomposition analysis showed that with few exceptions, the dispersion interaction is the dominant interaction, followed by the charge-transfer and polarization interactions. The affinities for OTV were greatly reduced …

Predictive Algorithm For Surgery Recommendation In Thoracolumbar Burst Fractures Without Neurological Deficits, Charlotte Dandurand, Nader Fallah, Cumhur F. Öner, Richard J. Bransford, Klaus Schnake, Alex R. Vaccaro, Lorin M. Benneker, Emiliano Vialle, Gregory D. Schroeder, Shanmuganathan Rajasekaran, Mohammad El-Skarkawi, Rishi M. Kanna, Mohamed Aly, Martin Holas, Jose A. Canseco, Sander Muijs, Eugen Cezar Popescu, Jin Wee Tee, Gaston Camino-Willhuber, Andrei Fernandes Joaquim, Ory Keynan, Harvinder Singh Chhabra, Sebastian Bigdon, Ulrich Spiegel, Marcel F. Dvorak

Department of Orthopaedic Surgery Faculty Papers

STUDY DESIGN: Predictive algorithm via decision tree.

OBJECTIVES: Artificial intelligence (AI) remain an emerging field and have not previously been used to guide therapeutic decision making in thoracolumbar burst fractures. Building such models may reduce the variability in treatment recommendations. The goal of this study was to build a mathematical prediction rule based upon radiographic variables to guide treatment decisions.

METHODS: Twenty-two surgeons from the AO Knowledge Forum Trauma reviewed 183 cases from the Spine TL A3/A4 prospective study (classification, degree of certainty of posterior ligamentous complex (PLC) injury, use of M1 modifier, degree of comminution, treatment recommendation). Reviewers' regions …

Edsuch: A Robust Ensemble Data Summarization Method For Effective Medical Diagnosis, Mohiuddin Ahmed, A. N. M. B. Rashid

Research outputs 2022 to 2026

Identifying rare patterns for medical diagnosis is a challenging task due to heterogeneity and the volume of data. Data summarization can create a concise version of the original data that can be used for effective diagnosis. In this paper, we propose an ensemble summarization method that combines clustering and sampling to create a summary of the original data to ensure the inclusion of rare patterns. To the best of our knowledge, there has been no such technique available to augment the performance of anomaly detection techniques and simultaneously increase the efficiency of medical diagnosis. The performance of popular anomaly detection …

Analysis Of The Outer Retinal Bands In Abca4 And Prph2-Associated Retinopathy Using Oct, Rachael C. Heath Jeffery, Johnny Lo, Jennifer A. Thompson, Tina M. Lamey, Terri L. Mclaren, John N. De Roach, Lauren N. Ayton, Andrea L. Vincent, Abhishek Sharma, Fred K. Chen

Research outputs 2022 to 2026

Purpose: To evaluate the outer retinal bands using OCT in ABCA4- and PRPH2-associated retinopathy and develop a novel imaging biomarker to differentiate between these 2 genotypes. Design: Multicenter case-control study. Participants: Patients with a clinical and genetic diagnosis of ABCA4- or PRPH2-associated retinopathy and an age-matched control group. Methods: Macular OCT was used to measure the thickness of the outer retinal bands 2 and 4 by 2 independent examiners at 4 retinal loci. Main Outcome Measures: Outcome measures included the thicknesses of band 2, band 4, and the band 2/band 4 ratio. Linear mixed modeling was used to make comparisons …

Public Acceptance Of Using Artificial Intelligence-Assisted Weight Management Apps In High-Income Southeast Asian Adults With Overweight And Obesity: A Cross-Sectional Study, Han Shi Jocelyn Chew, Palakorn Achananuparp, Palakorn Achananuparp, Nicholas W. S. Chew, Yip Han Chin, Yujia Gao, Bok Yan Jimmy So, Asim Shabbir, Ee-Peng Lim, Kee Yuan Ngiam

Research Collection School Of Computing and Information Systems

Introduction: With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods: 280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression. Results: 271 participant responses were …

Dynamic Prognosis Prediction For Patients On Dapt After Drug-Eluting Stent Implantation: Model Development And Validation, Fang Li, Laila Rasmy, Yang Xiang, Jingna Feng, Ahmed Abdelhameed, Xinyue Hu, Zenan Sun, David Aguilar, Abhijeet Dhoble, Jingcheng Du, Qing Wang, Shuteng Niu, Yifang Dang, Xinyuan Zhang, Ziqian Xie, Yi Nian, Jianping He, Yujia Zhou, Jianfu Li, Mattia Prosperi, Jiang Bian, Degui Zhi, Cui Tao

School of Medicine Faculty Publications

BACKGROUND: The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug-eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. METHODS AND RESULTS: We developed and validated a new AI-based pipeline using retrospective data of drug-eluting stent-treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum’s de-identified Clinformatics Data Mart Database (n=9978). The 36 months following drug-eluting stent implantation were …

De Novo Drug Design Using Transformer-Based Machine Translation And Reinforcement Learning Of An Adaptive Monte Carlo Tree Search, Dony Ang, Cyril Rakovski, Hagop S. Atamian

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The discovery of novel therapeutic compounds through de novo drug design represents a critical challenge in the field of pharmaceutical research. Traditional drug discovery approaches are often resource intensive and time consuming, leading researchers to explore innovative methods that harness the power of deep learning and reinforcement learning techniques. Here, we introduce a novel drug design approach called drugAI that leverages the Encoder–Decoder Transformer architecture in tandem with Reinforcement Learning via a Monte Carlo Tree Search (RL-MCTS) to expedite the process of drug discovery while ensuring the production of valid small molecules with drug-like characteristics and strong binding affinities towards …

Virgin Coconut Oil (Vco) Supplementation Relieves Symptoms And Inflammation Among Covid-19 Positive Adults: A Single-Blind Randomized Trial, Imelda Angeles-Agdeppa, Jacus S. Nacis, Fabian M. Dayrit, Keith V. Tanda

Chemistry Faculty Publications

A clinical study conducted in 2020 showed that virgin coconut oil (VCO) has been found effective in the rapid relief of COVID-19 symptoms and normalization of the C-reactive protein (CRP) concentration among probable and suspected cases of COVID-19. This present study aimed to validate those results and to evaluate the effects of VCO among COVID-19 patients through a 28-day randomized, single-blind trial conducted among 76 SARS-CoV-2 RT-PCR (reverse transcription-polymerase chain report)-confirmed adults, with VCO given as a COVID-19 adjunct therapy. The results showed that VCO recipients were free from symptoms and had normal CRP concentrations by day 14. In comparison, …

Identifying Patterns For Neurological Disabilities By Integrating Discrete Wavelet Transform And Visualization, Soo Yeon Ji, Sampath Jayarathna, Anne M. Perrotti, Katrina Kardiasmenos, Dong Hyun Jeong

Computer Science Faculty Publications

Neurological disabilities cause diverse health and mental challenges, impacting quality of life and imposing financial burdens on both the individuals diagnosed with these conditions and their caregivers. Abnormal brain activity, stemming from malfunctions in the human nervous system, characterizes neurological disorders. Therefore, the early identification of these abnormalities is crucial for devising suitable treatments and interventions aimed at promoting and sustaining quality of life. Electroencephalogram (EEG), a non-invasive method for monitoring brain activity, is frequently employed to detect abnormal brain activity in neurological and mental disorders. This study introduces an approach that extends the understanding and identification of neurological disabilities …

A Holistic Approach To Performance Prediction In Collegiate Athletics: Player, Team, And Conference Perspectives, Christopher Taber, S. Sharma, Mehul S. Raval, Samah Senbel, Allison Keefe, Jui Shah, Emma Patterson, Julie K. Nolan, N.S. Artan, Tolga Kaya

Exercise Science Faculty Publications

Predictive sports data analytics can be revolutionary for sports performance. Existing literature discusses players' or teams' performance, independently or in tandem. Using Machine Learning (ML), this paper aims to holistically evaluate player-, team-, and conference (season)-level performances in Division-1 Women's basketball. The players were monitored and tested through a full competitive year. The performance was quantified at the player level using the reactive strength index modified (RSImod), at the team level by the game score (GS) metric, and finally at the conference level through Player Efficiency Rating (PER). The data includes parameters from training, subjective stress, sleep, and recovery (WHOOP …

Site-Specific Space Use And Resource Selection By Black Vultures (Coragyps Atratus) In The Southeastern Usa, Betsy Evans, John S. Humphrey, Eric A. Tillman, Michael L. Avery, Bryan M. Kluever

USDA Wildlife Services: Staff Publications

North American populations of Black Vultures Coragyps atratus have increased and expanded their distribution in the southern and eastern USA. In conjunction with these patterns has been a rise in human–vulture conflicts. To improve our understanding of space use patterns and better inform management, we evaluated the movements of Black Vultures (n = 23) in the southeastern USA using a long-term GPS tracking database. Our specific objectives were to: (1) quantify home-range sizes in relation to season and geographical study location and (2) examine within-home-range resource selection to identify landscape and anthropogenic factors influencing roost and diurnal space use. …

Treatment With The Immunocontraceptive Vaccine, Gonacon, Induces Temporary Fertility Control In Free-Ranging Prairie Dog Populations In Colorado, Usa, Aaron B. Shiels, Jackson Runte, Emily W. Ruell, Douglas C. Eckery, Gary W. Witmer, Daniel J. Salkeld

USDA Wildlife Services: Staff Publications

Context

Prairie dogs (Cynomys spp.) are rodents enjoyed by some humans; yet, they cause crop and property damage, and carry zoonotic disease. Non-lethal control of prairie dogs is of interest in urban/suburban settings. The injectable immunocontraceptive vaccine GonaCon (active ingredient is gonadotropin-releasing hormone [GnRH]) has been shown to be effective at reducing fertility in equine and deer, and is a US EPA-registered vaccine for use in these ungulate species.

Aims

To conduct a replicated field study to test efficacy of GonaCon in black-tailed prairie dogs (C. ludovicianus), and if found to be efficacious, to help facilitate …

Comparison Of Ketamine-Xylazine, Butorphanol-Azaperone-Medetomidine, And Nalbuphine-Medetomidine-Azaperone For Raccoon (Procyon Lotor) Immobilization, Shylo R. Johnson, Christine K. Ellis, Chad Wickham, Molly R. Selleck, Amy T. Gilbert

USDA Wildlife Services: Staff Publications

Raccoons (Procyon lotor) are frequently handled using chemical immobilization in North America for management and research. In a controlled environment, we compared three drug combinations: ketamine-xylazine (KX), butorphanol-azaperone-medetomidine (BAM), and nalbuphinemedetomidine- azaperone (NalMed-A) for raccoon immobilization. In crossover comparisons, raccoons received a mean of the following: 8.66 mg/kg ketamine and 1.74 mg/kg xylazine (0.104 mL/kg KX); 0.464 mg/kg butorphanol, 0.155 mg/kg azaperone, and 0.185 mg/kg medetomidine (0.017 mL/kg BAM); and 0.800 mg/kg nalbuphine, 0.200 mg/kg azaperone, and 0.200 mg/kg medetomidine (0.020 mL/kg NalMed-A). Induction time was shortest with KX (mean6SE, 10.060.7 min) and longest with NalMed-A (13.061.3 min). …

Oral Rabies Vaccination Of Raccoons (Procyon Lotor) Across A Development Intensity Gradient In Burlington, Vermont, Usa, 2015–2017, Emily M. Beasley, Kathleen M. Nelson, Dennis Slate, Amy T. Gilbert, Frederick E. Pogmore, Richard B. Chipman, Amy J. Davis

USDA Wildlife Services: Staff Publications

Management of the raccoon rabies virus variant in North America is conducted primarily using oral rabies vaccination (ORV). When a sufficient proportion of the population is vaccinated (60%), rabies transmission can be eliminated. To date, ORV programs have successfully controlled and eliminated raccoon rabies in rural areas, but there has been less success in urban areas. We studied the proportions of rabies virus neutralizing antibodies (RVNA) in a raccoon (Procyon lotor) population during a 3-year ORV trial in developed areas of Burlington, Vermont, United States. We used a modified N-mixture model to estimate raccoon abundance, RVNA seroprevalence, and …

Recent Beak Evolution In North American Starlings After Invasion, Julia M. Zichello, Shelagh T. Deliberto, Paul Shrewsbury, Agnieszka A. Pierwola, Scott J. Werner

USDA Wildlife Services: Staff Publications

European starlings are one of the most abundant and problematic avian invaders in the world. From their native range across Eurasia and North Africa, they have been introduced to every continent except Antarctica. In 160 years, starlings have expanded into different environments throughout the world, making them a powerful model for understanding rapid evolutionary change and adaptive plasticity. Here, we investigate their spatiotemporal morphological variation in North America and the native range. Our dataset includes 1,217 specimens; a combination of historical museum skins and modern birds. Beak length in the native range has remained unchanged during the past 206 years, …

Lead Bioaccessibility And Commonly Measured Soil Characteristics (Detroit, Mi, Usa) – Phase 1, Sabrina R. Good, Allison R. Harris, Patrick Crouch, Conor T. Gowan, William D. Shuster, Shawn P. Mcelmurry

Open Data at Wayne State

Contaminated urban soil is one of the major contributors to child Pb exposure. To gain a better understanding of Pb risk in urban areas, composite samples were collected from 142 residential, privately owned, parcels in Detroit, Hamtramck, and Highland Park, Michigan, with approval from the property owners. The proximity of soil sampling and former smelter locations were also reported. Sample were collected from areas covered with turf grass. Four samples were collected, one from each cardinal direction (north, south, east, and west), 20 cm from an aluminum tent stake driven into the center of the sampling site. Soils were collected …

Assessing The Efficiency Of Local Rabies Vaccination Strategies For Raccoons (Procyon Lotor) In An Urban Setting, Guillaume Bastille-Rousseau, Nicole T. Gorman, Katherine M. Mcclure, Larissa Nituch, Tore Buchanan, Richard B. Chipman, Amy T. Gilbert, Kim M. Pepin

USDA Wildlife Services: Staff Publications

Raccoon rabies virus (RRV) has been managed using multiple vaccination strategies, including oral rabies vaccination and trap-vaccinate-release (TVR). Identifying a rabies vaccination strategy for an area is a nontrivial task. Vaccination strategies differ in the amount of effort and monetary costs required to achieve a particular level of vaccine seroprevalence (efficiency). Simulating host movement relative to different vaccination strategies in silico can provide a useful tool for exploring the efficiency of different vaccination strategies. We refined a previously developed individual-based model of raccoon movement to evaluate vaccination strategies for urban Hamilton, Ontario, Canada. We combined different oral rabies vaccination baiting …

Quantification Of Antiviral Drug Tenofovir (Tfv) By Surface-Enhanced Raman Spectroscopy (Sers) Using Cumulative Distribution Functions (Cdfs), Marguerite R. Butler, Jana Hrncirova, Meredith Clark, Sucharita Dutta, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive spectroscopic technique that generates signal-enhanced fingerprint vibrational spectra of small molecules. However, without rigorous control of SERS substrate active sites, geometry, surface area, or surface functionality, SERS is notoriously irreproducible, complicating the consistent quantitative analysis of small molecules. While evaporatively prepared samples yield significant SERS enhancement resulting in lower detection limits, the distribution of these enhancements along the SERS surface is inherently stochastic. Acquiring spatially resolved SERS spectra of these dried surfaces, we have shown that this enhancement is governed by a power law as a function of analyte concentration. Consequently, by definition, …

Evidence Of Direct Interaction Between Cisplatin And The Caspase-Cleaved Prostate Apoptosis Response-4 Tumor Suppressor, Krishna K. Raut, Samjhana Pandey, Gyanendra Kharel, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Prostate apoptosis response-4 (Par-4) tumor suppressor protein has gained attention as a potential therapeutic target owing to its unique ability to selectively induce apoptosis in cancer cells, sensitize them to chemotherapy and radiotherapy, and mitigate drug resistance. It has recently been reported that Par-4 interacts synergistically with cisplatin, a widely used anticancer drug. However, the mechanistic details underlying this relationship remain elusive. In this investigation, we employed an array of biophysical techniques, including circular dichroism spectroscopy, dynamic light scattering, and UV–vis absorption spectroscopy, to characterize the interaction between the active caspase-cleaved Par-4 (cl-Par-4) fragment and cisplatin. Additionally, elemental analysis was …

Cumulative Distribution Function And Spatially Resolved Surface-Enhanced Raman Spectroscopy For The Quantitative Analysis Of Emtricitabine, Jana Hrncirova, Marguerite R. Butler, Sucharita Dutta, Meredith R. Clark, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) has exceptional analytical sensitivity and selectivity. However, SERS irreproducibility presents an obstacle when using it for precise quantitative measurements. In this study, colloidal nanoparticles evaporated to dryness are used as a SERS active surface for the detection of the HIV drug emtricitabine (FTC; trade name Emtriva). Despite the irreproducibility of the SERS resulting from the stochastic process of evaporation, using a SERS scanning instrument, the SERS enhancement factors of spatially resolved spectra have a well-defined distribution of signals for a given analyte concentration. This distribution follows a power law function ranging from weak (very abundant signals) …

Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li

Computer Science Faculty Publications

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding …

Toying With Adapted Toys, Joshua King

WWU Honors College Senior Projects

My project is a design for an adapted toy that occupational therapists (OT) can use when working with kids. OTs are people who help others to be able to do daily tasks that they need to do to live their lives. This can look like helping a person who has been injured or has a disability to accomplish tasks like getting dressed or feeding themselves. It can also involve helping school children to improve their writing or to use assistive technology. My project started out as an idea from my mom who is an OT and was using a coffee …

Limitations Of Invasive Snake Control Tools In The Context Of A New Invasion On An Island With Abundant Prey, Shane R. Siers, Melia G. Nafus, Jereid E. Calaor, Rachel M. Volsteadt, Matthew S. Grassi, Megan Volsteadt, Aaron F. Collins, Patrick D. Barnhart, Logan T. Huse, Amy A. Yackel Adams, Diane L. Vice

USDA Wildlife Services: Staff Publications

In October 2020, a new population of invasive brown treesnakes (Boiga irregularis) was discovered on the 33-ha Cocos Island, 2.5 km off the south coast of Guam, United States. Cocos Island is a unique conservation resource, providing refuge for many lizards and birds, including endangered species, which were extirpated from mainland Guam by invasive predators including brown treesnakes. We sought to evaluate the usefulness of toxic baiting with acetaminophen-treated carrion baits and cage trapping, common tools for the control of brown treesnakes on mainland Guam, as potential eradication tools on Cocos Island. We evaluated multiple bait types and …

Decoding U.S. Tort Liability In Healthcare's Black-Box Ai Era: Lessons From The European Union, Mindy Duffourc, Sara Gerke

Faculty Scholarly Works

The rapid development of sophisticated artificial intelligence (“AI”) tools in healthcare presents new possibilities for improving medical treatment and general health. Currently, such AI tools can perform a wide range of health-related tasks, from specialized autonomous systems that diagnose diabetic retinopathy to general-use generative models like ChatGPT that answer users’ health-related questions. On the other hand, significant liability concerns arise as medical professionals and consumers increasingly turn to AI for health information. This is particularly true for black-box AI because while potentially enhancing the AI’s capability and accuracy, these systems also operate without transparency, making it difficult or even impossible …

Predictive Power Of Wastewater For Nowcasting Infectious Disease Transmission: A Retrospective Case Study Of Five Sewershed Areas In Louisville, Kentucky, Fayette Klaassen, Rochelle H. Holm, Ted Smith, Ted Cohen, Aruni Bhatnagar, Nicolas A. Menzies

Faculty Scholarship

Background: Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. Methods: We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. …

Swosu Research And Scholarly Activity Fair 2024, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) - Welcome to the Thirty-Second SWOSU Research and Scholarly Activity Fair! There are 61 poster presentations and 10 oral presentations involving over 100 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors encompassing activities from the SWOSU Departments of Biological Sciences, Chemistry & Physics, Engineering Technology, Kinesiology, Language & Literature, Mathematics, Music, Parks and Recreation Management, Pharmacy, Psychology, and Social Sciences.

Infusing Machine Learning And Computational Linguistics Into Clinical Notes, Funke V. Alabi, Onyeka Omose, Omotomilola Jegede

Mathematics & Statistics Faculty Publications

Entering free-form text notes into Electronic Health Records (EHR) systems takes a lot of time from clinicians. A large portion of this paper work is viewed as a burden, which cuts into the amount of time doctors spend with patients and increases the risk of burnout. We will see how machine learning and computational linguistics can be infused in the processing of taking clinical notes. We are presenting a new language modeling task that predicts the content of notes conditioned on historical data from a patient's medical record, such as patient demographics, lab results, medications, and previous notes, with the …

Automatic Hemorrhage Segmentation In Brain Ct Scans Using Curriculum-Based Semi-Supervised Learning, Solayman H. Emon, Tzu-Liang (Bill) Tseng, Michael Pokojovy, Peter Mccaffrey, Scott Moen, Md Fashiar Rahman

Mathematics & Statistics Faculty Publications

One of the major neuropathological consequences of traumatic brain injury (TBI) is intracranial hemorrhage (ICH), which requires swift diagnosis to avert perilous outcomes. We present a new automatic hemorrhage segmentation technique via curriculum-based semi-supervised learning. It employs a pre-trained lightweight encoder-decoder framework (MobileNetV2) on labeled and unlabeled data. The model integrates consistency regularization for improved generalization, offering steady predictions from original and augmented versions of unlabeled data. The training procedure employs curriculum learning to progressively train the model at diverse complexity levels. We utilize the PhysioNet dataset to train and evaluate the proposed approach. The performance results surpass those of …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Modeling The Effect Of Observational Social Learning On Parental Decision-Making For Childhood Vaccination And Diseases Spread Over Household Networks, Tamer Oraby, Andras Balogh

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

In this paper, we introduce a novel model for parental decision-making about vaccinations against a childhood disease that spreads through a contact network. This model considers a bilayer network comprising two overlapping networks, which are either Erdős–Rényi (random) networks or Barabási–Albert networks. The model also employs a Bayesian aggregation rule for observational social learning on a social network. This new model encompasses other decision models, such as voting and DeGroot models, as special cases. Using our model, we demonstrate how certain levels of social learning about vaccination preferences can converge opinions, influencing vaccine uptake and ultimately disease spread. In addition, …