Medicine and Health Sciences Commons^™

Interaction Of Cardiac Leiomodin With The Native Cardiac Thin Filament, Madison Little, Cristina M. Risi, Tania M. Larrinaga, Mason D. Summers, Tyler Nguyen, Garry E. Smith Jr., Jennifer Atherton, Carol C. Gregorio, Alla S. Kostyukova, Vitold E. Galkin

Department of Biomedical and Translational Sciences Faculty Publications

Every heartbeat depends on cyclical contraction-relaxation produced by the interactions between myosin-containing thick and actin-based thin filaments (TFs) arranged into a crystalline-like lattice in the cardiac sarcomere. Therefore, the maintenance of thin filament length is crucial for myocardium function. The thin filament is comprised of an actin backbone, the regulatory troponin complex and tropomyosin that controls interactions between thick and thin filaments. Thin filament length is controlled by the tropomodulin family of proteins; tropomodulin caps pointed ends of thin filaments, and leiomodin (Lmod) promotes elongation of thin filaments by a “leaky-cap” mechanism. The broader distribution of Lmod on the thin …

Implementing A Chatbot To Promote Hereditary Breast & Ovarian Cancer Genetic Screening In Women's Health: Identifying Barriers And Facilitators To Screening Adoption, Easton N. Wollney, Shireen Madani Sims, Luisel J. Ricks-Santi, Elizabeth Eddy, Daniel Wiesman, Carla L. Fisher

Department of Biomedical and Translational Sciences Faculty Publications

Background

To promote genetic screening among women at risk for hereditary breast and ovarian cancer (HBOC), the American College of Obstetricians and Gynecologists recommends that risk assessment be integrated into practice. Chatbots like the Genetic Information Assistant (Gia®) are increasingly implemented to expand access to hereditary genetic screening. Factors that impact chatbot implementation for HBOC risk screening and women's uptake are not fully realized. To refine implementation strategies prior to full scale implementation, we sought to identify women's perceived facilitators/barriers to adopting Gia screening in a rural population within a large healthcare system in the southern United States.

Methods

We …

A Modern Optimization Approach With Data-Driven Analytical Modeling For The Healthcare Business Segment (Hbs) From The S&P 500, Aditya Chakraborty, Chris Tsokos

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: The S&P consists of eleven business segments, which are classified according to the type of industry. The current study focuses on developing a non-linear analytical model for the Healthcare Business Segment (HBS) of the S&P 500, as a function of different economic & financial indicators. Materials and Methods: The analytical model used six financial indicators together with four economic indicators to predict the weekly average closing price (WCP) of HBS stocks. Johnson’s SB transformation corrected skewness, while desirability-based optimization identified indicator values maximizing WCP. The model’s performance and generalizability were validated through repeated 10-fold cross-validation. Results: All attributable contributors …

Pediatric Cancer Incidence, Temporal Trends, And Mortality In The United States By Health Disparities Indicators, Seer (1973-2014), Prachi P. Chavan, Laurens Holmes Jr.

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pediatric cancer incidence has been increasing in the United States, despite improvement in pediatric cancer survival. This steady increase in incidence trends is not completely understood but maybe associated with social and environmental factors. In this study we aimed to assess the cumulative incidence, temporal trends, and mortality rates in pediatric cancer. Additionally, we examined sub-group variability in both incidence and mortality rates. Methods: Data from Surveillance, Epidemiology, and End Results (SEER) −18 from 1973–2014 were used for the purpose of analysis in this study. Age-adjusted incidence rates were used to assess temporal trends in cancer among children aged < 1–19 years. Univariable and multivariable binomial regression models were used to examine the association between race and cancer mortality while adjusting for potential confounders. Results: There were 92,594 cancer diagnoses during this period. White children comprised 74,758, (80.7%), black children 10,030, (10.8%), and other races 6648, (7.2%). Overall the age-adjusted cumulative incidence was slightly higher among white children (16.4%) than black children (12.4%) and other (13.0%). Children aged 15–19 years and those in metropolitan regions were more likely to be diagnosed with pediatric cancer. Relative to females, males were 16% more likely to die from the disease [adjusted Risk Ratio (aRR): 1.16, 95% Confidence Interval (CI): 1.09–1.22]. Additionally, compared to white children, black children had higher mortality rates [(aRR): 1.37, 99% CI: 1.23–1.52]. Conclusions: There is an increasing trend in pediatric cancer incidence; while white children have the highest incidence, black children and males indicated a survival disadvantage, indicative of racial and sex variability in overall pediatric cancer in the United States.

Label Correlated Contrastive Learning For Medical Report Generation, Xinyao Liu, Junchang Xin, Bing Tian Dai, Qi Shen, Zhihong Huang, Zhiqiong Wang

Research Collection School Of Computing and Information Systems

Background and Objective: Automatic generation of medical reports reduces both the burden on radiologists and the possibility of errors due to the inexperience of radiologists. The model that utilizes attention mechanism and contrastive learning can generate medical reports by capturing both general and specific semantics. However, existing contrastive learning methods ignore the specificity of medical data, that is, a patient may suffer from multiple diseases at the same time. This means that the lack of fine-grained relationships for contrastive learning will lead to the problem of insufficient specificity. Methods: To address the above problem, a label correlated contrastive learning method …

Gamified Mhealth System For Evaluating Upper Limb Motor Performance In Children: Cross-Sectional Feasibility Study, Md Raihan Mia, Sheikh Iqbal Ahamed, Samuel Nemanich

Computer Science Faculty Research and Publications

Background: Approximately 17% of children in the United States have been diagnosed with a developmental or neurological disorder that affects upper limb (UL) movements needed for completing activities of daily living. Gold-standard laboratory assessments of the UL are objective and precise but may not be portable, while clinical assessments can be time-intensive. We developed MoEvGame, a mobile health (mHealth) gamification software system for the iPad, as a potential advanced technology to assess UL motor functions.

Objective: This feasibility study examines whether MoEvGame can assess children’s whole-limb movement, fine motor skills, manual dexterity, and bimanual coordination. The specific aims were to …

Establishing A Conventional Linac-Based Electron Flash Beam, Justin Defrancisco

Theses and Dissertations

Problems: A rediscovered radiotherapy technique, FLASH, involves increasing the dose rate to >40 Gy/s. For a given dose, FLASH is shown to decrease the normal tissue complication probability without affecting the tumor control probability. More preclinical studies are necessary to confirm and enable these desirable properties on humans. Current preclinical investigations have diverse constraints, requiring FLASH apparatuses with flexible parameters and accurate control. However, there are limited FLASH platforms available, the existing ones are costly. Our institution is not in possession of any such infrastructure. Even if available, dosimetry and beam control in FLASH are extremely lacking. There is …

Insights Into Factors Influencing Radical Coupling Chemistry Of Monolignols During Lignification And Induced Changes In Plant Secondary Metabolism, Rachel Poornima Sutherland

Theses and Dissertations--Chemistry

Lignin is a complex aromatic biopolymer and an important constituent in plant cell walls. The process of lignin biosynthesis, known as lignification, is poorly understood and challenging to study but has important implications in a variety of fields including sustainable energy, bioengineering, and materials science and is therefore of interest to pursue. In the final stage of lignification, H-, G-, and S-monolignols are oxidized by laccase and peroxidase enzymes to generate radical species that couple to form dimers and further oligomeric species to ultimately produce the lignin polymer. Biomimetic lignin model systems utilize in vitro oxidative coupling reactions as an …

Redox Control In A Fused Electron Transfer Flavoprotein From A Thermophilic Archaeon And Expanded Significance Of A Hydrogen Bond From A Conserved Histidine Residue That Contributes To Flavin Redox Tuning And Activation For Covalent Modification, Debarati Das

Theses and Dissertations--Chemistry

In absence of O₂ as terminal electron acceptors in anaerobic bacteria and archaea, carbohydrate metabolism is 15 times less efficient compared to aerobic energy metabolism resulting in energy deficit conditions. Despite their meager resources these anaerobes were able to generate H₂ and a chemiosmotic potential able to drive energy demanding reactions such as CO₂ or N₂ fixation. These observations raised concerns as production of high energy reductants (H₂) from mediocre fuels (NADH) defied the laws of thermodynamics.

In 2008, a known mechanism “electron bifurcation” but with flavins as redox mediators instead of quinones was …

Monte Carlo Modeling Of Spin Polarized Photoemission From Gaas At Low Temperatures And Positive Electron Affinity Surfaces, John Rison Callahan

Graduate Research Theses & Dissertations

Research and development of new photocathode materials are essential to the continuing success and productivity of accelerator technology. High-quality photocathodes characterized by high quantum efficiencies, long lifetimes, low mean transverse energies, and robustness to vacuum environments and operation loads are becoming increasingly essential to the successful operation of the next generation of high brightness accelerator applications. For nuclear and high-energy physics experiments and other applications that rely on spin-polarized electron beams, photocathodes must also demonstrate high electron spin polarizations. The development of state of-the-art spin-polarized photocathodes will require both development of methods to improve the quality of already existing cathode …

Determination Of Structural Factors Contributing To Protection Of Zinc Fingers In Estrogen Receptor Α Through Molecular Dynamic Simulations, Patricia B. Lutz, Wesley R. Coombs, Craig A. Bayse

Chemistry & Biochemistry Faculty Publications

The ERα transcription factor that induces tumor growth is a potential target for breast cancer treatment. Each monomer of the ERα DNA-binding domain (ERαDBD) homodimer has two conserved (Cys)₄-type zinc fingers, ZF1 (N-terminal) and ZF2 (C-terminal). Electrophilic agents release Zn²⁺ by oxidizing the coordinating Cys of the more labile ZF2 to inhibit dimerization and DNA binding. Microsecond-length molecular dynamics (MD) simulations show that greater flexibility of ZF2 in the ERαDBD monomer leaves its Cys more solvent accessible and less shielded from electrophilic attack by sulfur-centered hydrogen bonds than ZF1 which is buried in the protein. In the …

Phytochemical Analysis, Antioxidant, And Antibacterial Properties Of Partition Fractions Of Adansonia Digitata And Annona Muricata Extracts Using Chloroform, Ethyl Acetate, Ethanol, And Aqueous Solvent Systems, Fagbohun Oyenike Bushirat, Hassan Abdusalam Adewuyi, Sakariyau Adio Waheed, Maryam Nana Musa, Timothy God-Giveth Olusegun, Ayomide Babatunde Ishola, Agumage Idoko, Adeola Victor Kolawole, Adesanmi Adefunmilayo Oluwatuyi, Sarah Ngozi Agwasim

Chemistry & Biochemistry Faculty Publications

Adansonia digitata and Annona muricata are traditionally used medicinal plants with reported pharmacological properties. In this study, we aimed to elucidate the phytochemical composition, antioxidant activity, and antibacterial properties of partition fractions of Adansonia digitata and Annona muricata extracts obtained using chloroform, ethyl acetate, ethanol, and aqueous solvent systems. The plant extracts were successively partitioned using chloroform, ethyl acetate, ethanol, and aqueous solvent systems. Phytochemical analysis was performed using standard methods. Antioxidant activity was evaluated using FRAP and DPPH assays. Antibacterial activity was assessed using agar well diffusion and MIC determination. Phytochemical analysis revealed the presence of alkaloids (10.2-15.6%), flavonoids …

The Importance Of Solution Studies For The Structural Characterization Of The Enterovirus 5' Cloverleaf, Morgan G. Daniels, Meagan E. Werner, Xiaobing Zuo, Steven M. Pascal

Chemistry & Biochemistry Faculty Publications

Enteroviruses initiate genomic replication via a highly conserved mechanism that is controlled by an RNA platform, also known as the 5' cloverleaf (5'CL). Here, we present a biophysical analysis of the 5'CL conformation of three enterovirus serotypes under various ionic conditions, utilizing CD spectroscopy, size-exclusion chromatography, and small-angle X-ray scattering. In general, a tendency toward a smaller monomeric hydrodynamic radius in the presence of salts was observed, but the exact structural signature of each 5'CL varied depending upon the serotype. Rhinovirus B14 (RVB14) exhibited at least two monomeric conformations and a low propensity for dimerization, while poliovirus 1 (PV1) showed …

40 Years Passing By In (A) “Heartbeat”, Christopher Janney

Monsoon: South Asian Studies Association Journal

This article outlines the forty-year history go Christopher Janney’s iconic performance work “HeartBeat.” Trained as an architect and jazz musician, Janney combines these two disciplines to create large interactive light/sound installations and performances. On the one hand, he attempts to make architecture more like music, more “alive” using real-time sensing devices as on his “Harmonic Convergence” installation on the Miami International Airport. On the other hand, he attempts to make music more like architecture, more physical more visual. In his “HeartBeat” performance, a dancer wears a heartbeat device that amplifies his/her heartbeat in “real time.” Over this pulse, live musicians …

Yoga Sūtra Book Four And The Yogabindu, Christopher Key Chapple

Monsoon: South Asian Studies Association Journal

Four themes from the fourth pāda of Patañjali’s Yoga Sūtra are examined here: karma (IV:2-13), individuality (IV:16), humility (IV:20-22), and freedom (IV:29-34). Affirmations and variant interpretations of these four are provided from Haribhadra Virahāṅka’s Yogabindu, most likely composed a century or two later.

Collective Karma: From The Yogasūtra To Taylor Swift, Zoë Slatoff

Monsoon: South Asian Studies Association Journal

The Indian knowledge traditions speak at length about karma, which is divided into three categories—accumulated (saṃcita), ripe (prārabdha), and future (kriyamāṇa). While much is said about our individual karma and how it affects our repeated reincarnation in cyclic existence, how does this affect others and how do others affect us? In other words, as this paper explores, what is our reciprocal and collective karma?

Painting Liberation: A Visual Ontology Of The Interplay Of Mind And Consciousness In Book Four Of The Yoga Sūtras, Melissa Townsend

Monsoon: South Asian Studies Association Journal

This presentation explores how artistic practice can illuminate philosophical questions about the nature of mind, consciousness, and liberation as articulated in Book Four of the Yoga Sūtras of Patañjali. Through a series of paintings that visually translate these sūtras, I propose that art offers a unique, experiential means of engaging with the complex relationship between citta (mind) and puruṣa (consciousness).

The paintings function as a form of “visual ontology,” inviting viewers to engage with abstract philosophical concepts in a sensory, tangible way. By depicting the interplay between the mutable processes of the mind and the unchanging awareness of consciousness, these …

A Case Study Using The Transparency Framework And Artificial Intelligence To Promote Effective Writing And Student Success In A Writing-Intensive Course, Elizabeth A. Brown, Maria Kronenburg, Ashlee Steeley, Diana Tagbor

Health Behavior, Policy & Management Faculty Publications

Program evaluation data suggest that undergraduate students struggle with writing in a clear and concise manner and appropriately citing. Faculty implemented the plan-do study-act cycle to pilot the Transparency in Learning and Teaching (TILT) project framework and to explore the use of artificial intelligence (AI) and discuss approaches to using AI, along with the TILT framework, in a writing-intensive course to identify the pros and cons of using ChatGPT in an online classroom. The TILT framework reinforces adult learning by helping students clearly understand the assignment's purpose and establish a clear relationship between assignment and students' professional lives. Faculty encouraged …

A Qualitative Analysis Of College Students' Interest In Mhealth Solutions, Leslie Hoglund, Craig M. Becker, Cara Tonn

Health Behavior, Policy & Management Faculty Publications

This study explores college students' perceptions of an AI-driven mHealth application designed to promote well-being. With rising mental health challenges in academic settings, students increasingly seek digital tools that provide holistic support for physical, mental, and financial health. Through focus groups, this qualitative study examines students' preferences for personalized health tracking, educational content, and flexible reminders within a private, supportive community. Key findings emphasize students' desire for a balanced, all-in-one app that integrates health and wellness tools without overwhelming them with notifications. Students also highlighted the importance of social media integration for outreach, though concerns were raised about potential stress …

Check Your Data Before You Wreck Your Model: The Impact Of Careless Responding On Substance Use Data Quality, Abby L. Braitman, Anna M. Petrey, Jennifer L. Shipley, Rachel Ayala Guzman, Emily Renzoni, Alison Looby, Adrian J. Bravo

Psychology Faculty Publications

Background: The accuracy of survey responses is a concern in research data quality, especially in college student samples. However, examination of the impact of removing participants from analyses who respond inaccurately or carelessly is warranted given the potential for loss of information or sample diversity. This study aimed to understand if careless responding varies across a number of demographic indices, substance use behaviors, and the timing of survey completion.

Method: College students (N = 5809; 70.7% female; 75.7% White, non-Hispanic) enrolled in psychology classes from six universities completed an online survey assessing a variety of demographic and substance use-related information, …

Generation Z’S Perception Of Skin Cancer And How It Relates To Climate Change, Piercen Bogolea

Honors Undergraduate Theses

Skin cancer is the most common cancer worldwide, and climate change has been identified as a significant contributor. Preventative action early on can help reduce occurrence, but it is unknown if Generation Z is aware of this and is taking the necessary action now to protect themselves. This research aims to gauge the perception of Generation Z on the severity of skin cancer, the relationship between climate change and skin cancer, and the prevalence of preventative measures being taken. A survey was distributed to students aged 18 to 27 enrolled at the University of Central Florida through mixed sampling. The …

An Explainable Ai And Optimized Multi-Branch Convolutional Neural Network Model For Eye Anemia Diagnosis, Kamel K. Mohammed, Nadia Dahmani, Rania Ahmed, Ashraf Darwish, Aboul Ella Hassanien

All Works

This paper proposes a novel, non-invasive approach to diagnosing eye anemia using deep learning techniques. Traditional methods, reliant on invasive procedures like venipuncture, are costly and can cause patient discomfort. Our model leverages a multi-branch convolutional neural network (CNN) architecture, incorporating the Hippopotamus Optimization (HO) algorithm and multiclass support vector machines (SVMs) for enhanced accuracy. To address data imbalance, we employ the Synthetic Minority Oversampling Technique (SMOTE) and data augmentation. The model is trained and evaluated on a dataset of 211 eye images. The model achieves a remarkable 97.06% accuracy, with a Receiver Operating Characteristic (ROC) curve demonstrating an Area …

Corporate ‘Capture Strategies’ Impacting Human And Ecosystem Health, Alex T. Ford, Marlene Ågerstrand, Michael G. Bertram, Miriam L. Diamond, Rainer Lohmann, Andreas Schäffer, Martin Scheringer, Gabriel Sigmund, Anna Soehl, Maria Clara V.M. Starling, Noriyuki Suzuki, Marta Venier, Penny Vlahos

Graduate School of Oceanography Faculty Publications

The concept of regulatory capture has been extensively studied in academic literature, primarily within the social sciences. This phenomenon has been increasingly discussed in the environmental sciences as the impacts of regulatory capture on human and ecosystem health have become increasingly apparent. Regulatory capture is just one tactic employed by vested interests in the strategy of delaying, weakening, or abolishing policies designed to protect the public interest. Here, we define capture strategies as ‘the act of influencing individuals, organizations, or governments to prioritize corporate interests over those of human and ecosystem health’. Similar to the evolution of terms like whitewashing …

Generating Real-World Evidence In Early Alzheimer's Disease: Considerations For Applying The Target Trial Emulation Framework To Study The Safety Of Anti-Amyloid Therapies, Xiaojuan Li, Sonal Singh, Bahareh Rasouli, Jennifer Lyons, Noelle M. Cocoros, Richard Platt, Ivan Abi-Elias, Jerry H. Gurwitz

Department of Medicine Faculty Publications

Anti-amyloid beta monoclonal antibodies (anti-Aβ mAbs) have received approval from the US Food and Drug Administration for the treatment of patients with mild cognitive impairment or mild dementia due to Alzheimer's disease (collectively known as early AD) based on evidence from clinical trials. However, whether findings from these trials are generalizable to the real world is uncertain. We need reliable evidence on the real-world safety of these treatments to inform decision making for clinicians, patients, and caregivers. Using lecanemab as an exemplar, we outline the key considerations in designing and implementing an observational study on safety and utilization outcomes using …

Group Antenatal Care Positively Transforms The Care Experience: Results Of An Effectiveness Trial In Malawi, Crystal L. Patil, Kathleen F. Noor, Esnath Kapito, Li C. Liu, Xiaohan Mei, Elizabeth Chodzaza, Genesis Chorwe-Sungani, Ursula Kafuulafula, Elizabeth T. Abrams, Allissa Desloge, Ashley Gresh, Rohan D. Jeremiah, Dhruvi R. Patel, Anne Batchelder, Heidy Wang, Jocelyn Faydenko, Sharon S. Rising, Ellen Chirwa

Department of Medicine Faculty Publications

Background

We developed and tested a Centering-based group antenatal (ANC) model in Malawi, integrating health promotion for HIV prevention and mental health. We present effectiveness data and examine congruence with only the Group ANC theory of change model, which identifies key processes as supportive relationships, empowered partners in learning and care, and meaningful services, leading to better ANC experiences and outcomes.

Methods

We conducted a hybrid effectiveness-implementation trial at seven clinics in Blantyre District, Malawi, comparing outcomes for 1887 pregnant women randomly assigned to Group ANC or Individual ANC. Group effects on outcomes were summarized and evaluated using t-tests, Mann-Whitney, …

Calcium Carbonate Microparticles As Acid Responsive Targeted Drug Delivery Carriers For Oral Diseases And Its Anti-Bacterial Activity, Hem Raj Joshi

Dissertations and Theses

Dental diseases are mostly caused by bacterial infections in the teeth, forming biofilms that release acids and decay the enamel of the teeth. More than half of the world's population were affected by oral diseases, including periodontitis (gum disease), dental caries (cavities), and oral cancer. Chlorhexidine (CHX) is the mostly used antimicrobial drug for dental diseases, but its overexposure to the healthy teeth causes many side effects, such as tooth staining, taste alteration, and many more. Taking advantage of the acidic environment of infected teeth, we designed a pH responsive targeted drug delivery system using calcium carbonate microparticles (CCMPs) as …

The Reliability Gap: How Traditional Search Engines Outperform Artificial Intelligence (Ai) Chatbots In Rosacea Public Health Information Quality, Houston C. Nelson, Morgan T. Beauchamp, April A. Pace

Department of Medicine Faculty Publications

Background: The internet has become a primary source of health information for the public, with important implications for patient decision-making and public health outcomes. However, the quality and readability of this content vary widely. With the rise of generative artificial intelligence (AI) tools such as ChatGPT and Gemini, new challenges and opportunities have emerged in how patients access and interpret medical information.

Objective: To evaluate and compare the quality, credibility, and readability of consumer health information provided by traditional search engines (Google, Bing) and generative AI platforms (ChatGPT, Gemini) using three validated instruments: DISCERN, JAMA Benchmark Criteria, and Flesch-Kincaid Readability …

Automating The Amino Acid Identification In Elliptical Dichroism Spectrometer With Machine Learning, Ridhanya Sree Balamurugan, Yusuf Asad, Tommy Gao, Dharmakeerthi Nawarathna, Umamaheswara Rao Tida, Dali Sun

Electrical & Computer Engineering Faculty Publications

Amino acid identification is crucial across various scientific disciplines, including biochemistry, pharmaceutical research, and medical diagnostics. However, traditional methods such as mass spectrometry require extensive sample preparation and are time-consuming, complex and costly. Therefore, this study presents a pioneering Machine Learning (ML) approach for automatic amino acid identification by utilizing the unique absorption profiles from an Elliptical Dichroism (ED) spectrometer. Advanced data preprocessing techniques and ML algorithms to learn patterns from the absorption profiles that distinguish different amino acids were investigated to prove the feasibility of this approach. The results show that ML can potentially revolutionize the amino acid analysis …

Mxene-Based Materials For Enhanced Water Quality: Advances In Remediation Strategies, Ali Mohammad Amani, Milad Abbasi, Atena Najdian, Farzaneh Mohamadpour, Seyed Reza Kasaee, Hesam Kamyab, Shreeshivadasan Chelliapan, Mostafa Shafiee, Lobat Tayebi, Ahmad Vaez, Atefeh Najafian, Ehsan Vafa, Sareh Mosleh-Shirazi

Electrical & Computer Engineering Faculty Publications

Two-dimensional MXenes are promising candidates for water treatment because of their large surface area (e.g., exceeding 1000 m²/g for certain structures), high electrical conductivity (e.g., >1000 S/m), hydrophilicity, and chemical stability. Their strong sorption selectivity and effective reduction capacity, exemplified by heavy metal adsorption efficiencies exceeding 95 % in several studies, coupled with facile surface modification, make them suitable for removing diverse contaminants. Applications include the removal of heavy metals (e.g., achieving >90 % removal of Pb(II)), dye removal (e.g., demonstrating >80 % removal of methylene blue), and radioactive waste elimination. Furthermore, 3D MXene architecture exhibit enhanced performance in antibacterial …

Differentiating Opioid Use Disorder From Healthy Controls Via Ml Analysis Of Rs-Fmri Networks, Ahmed Temtam, Megan A. Witherow, Liangsuo Ma, M. Shibly Sadique, F. Gerard Moeller, C. Kenneth, Dianne Wright, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Objectives/Goals: This work aims to identify functional brain networks that differentiate opioid use disorder (OUD) subjects from healthy controls (HC) using machine learning (ML) analysis of resting-state fMRI (rs-fMRI). We investigate the default mode network (DMN), salience network (SN), and executive control network (ECN), as well as demographic features. Methods/Study Population: This work uses high-resolution rs-fMRI data from a National Institute on Drug Abuse study (IRB #HM20023630) with 31 OUD and 45 HC subjects. We extract rs-fMRI blood oxygenation level-dependent (BOLD) features from the DMN, SN, and ECN. The Boruta ML algorithm identifies statistically significant features and brain activity mapping …