Digital Commons Network^™

Scope And Mechanism Of The Ruthenium-Catalyzed Sp3 C–H Coupling Reaction Of 2-Alkylindoles With Enones For The Synthesis Of Carbazole Derivatives, Krishna Prasad Gnyawali, Mina Son, Donghun Hwang, Nuwan Asanka Pannilawithana, Mu-Hyun Baik, Chase S. Yi

Chemistry Faculty Research and Publications

The catalytic system consisting of a cationic Ru–H complex 1 and 3,4,5,6-tetrachloro-1,2-benzoquinone (L1) was found to be highly effective for the dehydrative sp³ C–H coupling reaction of 2-alkyl substituted indoles with enones to form 2,4-disubstituted carbazole products. The analogous coupling reaction of 2-alkylindoles with linear enones bearing the cyclic olefinic group afforded tetracyclic carbazole products. A normal deuterium kinetic isotope effect was measured from the coupling reaction of 1,2-dimethylindole versus 1-methyl-2-(methyl-d₃)indole with (E)-3-penten-2-one (k_H/k_D = 2.5). The Hammett plot was constructed from the reaction of para-substituted …

Isotonic Phase I Cancer Clinical Trial Design Utilizing Patient-Reported Outcomes, Nolan A Wages, Ruitao Lin

Faculty, Staff and Student Publications

This article considers the concept of designing Phase I clinical trials using both clinician- and patient-reported outcomes to adaptively allocate study participants to tolerable doses and determine the maximum tolerated dose (MTD) at the study conclusion. We describe a new isotonic patient-reported outcome (PRO-ISO) Phase I design with the flexibility of allocating patients to lower, more tolerable regimens if a large number of PRO-DLT events are seen at higher doses. We conduct simulation studies of the operating characteristics of the design and compared them to the patient-reported outcomes continual reassessment method (PRO-CRM). We illustrate that the PRO-ISO makes appropriate dose …

Wnt7a, Naomi M Calhoun, Richard R Behringer

Faculty, Staff and Student Publications

WNT7A regulates numerous developmental processes. It can activate canonical and non-canonical signaling depending on context. It is expressed in the developing central nervous system, limb buds, reproductive organs, and other tissues. Spontaneous and targeted Wnt7a mutations in mouse models resulted in abnormal limbs, defects in male and female reproductive tract organs, infertility, and defects in cerebellar axon remodeling. In zebrafish, wnt7aa mutants exhibited neurogenesis and angiogenesis defects in the central nervous system. In humans, recessive WNT7A missense and nonsense mutations resulted in severe limb and pelvic bone defects. Alterations in WNT7A expression correlated with multiple types of cancer.

Bismuth-Infused Perivascular Wrap Facilitates Delivery Of Mesenchymal Stem Cells And Attenuation Of Neointimal Hyperplasia In Rat Arteriovenous Fistulas, Allan John R Barcena, Joy Vanessa D Perez, Marvin R Bernardino, Jossana A Damasco, Erin Marie D San Valentin, Carleigh Klusman, Benjamin Martin, Gino Martin Canlas, Francisco M Heralde, Natalie Fowlkes, Richard R Bouchard, Jizhong Cheng, Steven Y Huang, Marites P Melancon

Faculty, Staff and Student Publications

BACKGROUND: Mesenchymal stem cells (MSCs) have emerged as novel therapies for supporting arteriovenous fistula (AVF) maturation, and bioresorbable polymeric scaffolds have enabled sustained MSC delivery into maturing AVFs. However, the radiolucency of biopolymeric wraps prevents in vivo monitoring of their integrity and location, hindering long-term preclinical investigations.

METHODS: We infused bismuth nanoparticles (BiNPs) into polycaprolactone (PCL) to fabricate an electrospun perivascular wrap capable of MSC delivery and conducive to longitudinal monitoring using conventional imaging. We tested the wraps' effects on the attenuation of markers of neointimal hyperplasia (i.e., endothelial dysfunction, hypoxia, and inflammation), the leading cause of AVF failure, in …

Editorial: Women In Antimicrobials, Resistance And Chemotherapy: 2023, Cindy Shuan Ju Teh, Krassimira R. Hristova, Ana R. Freitas

Biological Sciences Faculty Research and Publications

No abstract provided.

Disparities In Breast Cancer Detection Modalities And Outcomes Among Geriatric Female Cancer Patients, Zhaoli Liu, Mathilda Nicot-Cartsonis, Biai D E Digbeu, Daoqi Gao, Sharon H Giordano, Yong-Fang Kuo

Faculty, Staff and Student Publications

This study examined racial and geographic disparities in breast cancer detection modalities (screening-, diagnostic-, or non-mammography) with cancer stage and mortality. A retrospective cohort study was conducted using Texas Cancer Registry-Medicare linkage data for geriatric women. Cancers detected through screening and diagnostic mammography had 43 % (95 % CI, 39 %-46 %, p < .0001) and 31 % (95 % CI, 27 %-35 %, p < .0001) lower all-cause mortality, and 49 % (95 % CI, 41 %-54 %, p < .0001) and 37 % (95 % CI, 32 %-43 %, p < .0001) lower cancer-specific mortality, respectively, compared to non-mammography-detected breast cancers. Patients from rural areas were 17 % (95 % CI, 1.06 - 1.29) more likely to be diagnosed with mid- (p = .0023) and advanced stage (p = .003) cancers compared to their urban counterparts. Racial or geographic disparities in cancer detection modalities with associated mortality no longer exist after adjusting for covariates. Healthcare professionals can leverage these findings to promote rural cancer health equity.

Organ Of Corti Macrophages: A Distinct Group Of Cochlear Macrophages With Potential Roles In Supporting Cell Degeneration And Survival, Mengxiao Ye, Celia Zhang, Dalian Ding, Guang-Di Chen, Henry J Adler, Rania Sharaf, Bo Hua Hu

Faculty, Staff and Student Publications

Macrophages are the primary immune cells in the cochlea, essential for maintaining cochlear homeostasis and orchestrating inflammatory responses to pathological events. Although these cells have been found in various parts of the cochlea, their presence in the organ of Corti, a critical structure for acoustic sensing, remains poorly understood. The present study was designed to examine macrophage responses to ototoxic drug-induced cochlear damage and age-related cochlear degeneration, with a particular focus on the pathological conditions that trigger macrophage recruitment into the organ of Corti. We used a model of ototoxicity induced by cyclodextrin, a cyclic oligosaccharide known for its ability …

A Cytotoxic Peptide-Drug Conjugate For Tumor-Specific Delivery Of Co-Injected Molecules, Norio Miyamura, Chisato M Yamazaki, Yasuaki Anami, Kyoji Tsuchikama, Kazuki N Sugahara

Faculty, Staff and Student Publications

An ideal cancer therapy enhances anti-tumor effects while minimizing side effects. iRGD, a non-cytotoxic peptide that activates a tumor-specific molecular transport machinery, promotes the penetration of co-injected drugs into tumor tissues. Clinical trials have demonstrated its potential as a tumor-specific delivery scaffold and potentiator of anti-cancer agents. In this study, we synthesized an iRGD conjugate containing monomethyl auristatin F (MMAF), a highly toxic antimitotic agent, and characterized its dual function as a tumor-specific cytotoxic agent and co-injected drug delivery scaffold. The iRGD-MMAF conjugate internalized and killed cultured tumor cells in an αv integrin-dependent manner. When injected systemically, iRGD-MMAF homed selectively …

Integrating Multi-Omics Data To Uncover Prostate Tissue Dna Methylation Biomarkers And Target Genes For Prostate Cancer Risk, Shuai Liu, Jingjing Zhu, Dylan Green, Hua Zhong, Quan Long, Chong Wu, Liang Wang, Youping Deng, Lang Wu

Faculty, Staff and Student Publications

Previous studies have indicated that specific CpG sites may be linked to the risk of prostate cancer (PCa) by regulating the expression of PCa target genes. However, most existing studies aim to identify DNA methylation (DNAm) biomarkers through blood tissue genetic instruments, which impedes the identification of relevant biomarkers in prostate tissue. To identify PCa risk-associated CpG sites in prostate tissue, we established genetic prediction models of DNAm levels using data from normal prostate samples in the GTEx (N = 108) and assessed associations between genetically predicted DNAm in prostate and PCa risk by studying 122,188 cases and 604,640 controls. …

The Human Spinothalamic Tract: Lessons From Cordotomy, Anthony K Allam, Michael Benjamin Larkin, Ishan A Patel, Mohammed Hasen, David Mears, Patrick Dougherty, Ashwin Viswanathan

Faculty, Staff and Student Publications

The spinothalamic tract has long been known as a primary conductor of nociceptive information, with its anatomical and physiological understanding evolving over centuries of research. This comprehensive review traces the history of the spinothalamic tract beginning with Brown-Sequard’s 1860 report of contralateral analgesia following a hemisection of the spinal cord. As clinical and surgical interventions, such as cordotomies have advanced, so did our understanding of the spinothalamic tract’s function and anatomy. The spinothalamic tract’s role as a crossed pathway conducting pain and temperature sensations was solidified by the mid-20th century. However, intricate details of its somatotopic arrangement, anatomical distributions and …

Normative Laboratory Value Ranges In Pediatric Patients Who Underwent Evaluation For Mis-C, Thomas Graf, Nathan M Money, Sindhoosha Malay, Nori Minich, Risa Bochner, Bari Winik, Ron Kaplan, Jennifer Y Colgan, Erin Aldag, Ryan O' Sullivan, Guliz Erdem, Allayne Stephans

Faculty, Staff and Student Publications

Background and objectives: Diagnosis of multisystem inflammatory syndrome in children (MIS-C) is challenging due to symptom overlap with other common conditions. The primary objective of this multicenter study was to establish normative laboratory values in MIS-C patients and compare to patients evaluated for MIS-C who had other final diagnoses.

Methods: Five hospitals reviewed records of a cohort of patients 6 months to 18 years old who were evaluated for MIS-C between March 31st 2020 and February 1st 2022. Patient demographics, clinical presentation, and laboratory values were compared in patients with a final diagnosis of MIS-C versus all other conditions. Patients' …

Three-Dimensional Deep Learning Normal Tissue Complication Probability Model To Predict Late Xerostomia In Patients With Head And Neck Cancer, Hung Chu, Suzanne P M De Vette, Hendrike Neh, Nanna M Sijtsema, Roel J H M Steenbakkers, Amy Moreno, Johannes A Langendijk, Peter M A Van Ooijen, Clifton D Fuller, Lisanne V Van Dijk

Faculty, Staff and Student Publications

Purpose: Conventional normal tissue complication probability (NTCP) models for patients with head and neck cancer are typically based on single-value variables, which, for radiation-induced xerostomia, are baseline xerostomia and mean salivary gland doses. This study aimed to improve the prediction of late xerostomia by using 3-dimensional information from radiation dose distributions, computed tomography imaging, organ-at-risk segmentations, and clinical variables with deep learning (DL).

Methods and materials: An international cohort of 1208 patients with head and neck cancer from 2 institutes was used to train and twice validate DL models (deep convolutional neural network, EfficientNet-v2, and ResNet) with 3-dimensional dose distribution, …

Bronchoalveolar Lavage Cell Percentages As Diagnostic Markers Of Immune Checkpoint Inhibitor Pneumonitis, Mahnoor Mir, Felipe Soto, Pedro Antonio Amezcua Gomez, Rodrigo Del Rio Arroyo, Adarsh Suresh, Amber Su, Qiong Gan, John Stewart, Roberto Adachi, Diwakar D Balachandran, Lara Bashoura, Roberto F Casal, Burton F Dickey, George A Eapen, Scott E Evans, Horiana Grosu, Carlos A Jimenez, Julie Lin, David E Ost, Bruce F Sabath, Vickie R Shannon, Aung Naing, Jianjun Gao, Jia Wu, Karthik Suresh, Saadia A Faiz, Mehmet Altan, Ajay Sheshadri

Faculty, Staff and Student Publications

Introduction: Diagnostic biomarkers for immune checkpoint inhibitor pneumonitis (ICIP) are lacking. Bronchoalveolar lavage (BAL) lymphocytosis has been associated with ICIP, but studies have not evaluated BAL lymphocytosis as a diagnostic biomarker for ICIP.

Purpose: This study aimed to measure the association of BAL immune cell percentage with ICIP and test its performance as a diagnostic biomarker.

Methods: We performed a retrospective chart review of 476 patients treated with ICIs for solid organ or hematologic malignancies who underwent BAL between 2016 and 2022. Two independent reviewers, blinded to the results of BAL cell percentage, confirmed the diagnosis of ICIP or other …

Deep Dive Into Targeted Therapies: Understanding Idh1-Mutant Aml Treatments [Podcast], Amer M Zeidan, Courtney Dinardo

Faculty, Staff and Student Publications

This podcast episode reviews recent advances in the treatment of IDH1-mutant acute myeloid leukemia (AML), focusing on the mechanisms, efficacy, and safety profiles of approved IDH1 inhibitors. The purpose is to present expert insights and clinical data from key trials that underscore the clinical benefits of these targeted therapies. Through discussion of key findings from pivotal clinical trial studies, including data supporting the use of these agents in both newly diagnosed and relapsed or refractory (R/R) settings, the episode highlights significant outcomes such as increased overall response and prolonged duration of remission in patients treated with IDH1 inhibitors. The analysis …

Exploring The Role Of Boundary Infrastructures In Facilitating Learning In A Research-Practice Partnership, Jody Clarke-Midura, Alireza Zandi, Mimi Recker

Publications

This study examines how boundary infrastructures in Research-Practice Partnerships (RPPs) facilitate learning and collaboration between a rural school district and two universities. Using the Learning at the Boundaries framework, we analyze design team meetings, teacher feedback, and co-designed curricular materials. Our findings highlight the roles of boundary spanners, practices, and objects in bridging gaps among stakeholders and fostering sustainable collaboration. This research contributes to the learning sciences by documenting effective processes for organizational learning, emphasizing the importance of structured co-design in educational improvement.

In-Person Versus Peer-Coordinated Virtual Health Coaching For Metabolic And Behavioral Outcomes In Women In Sober Living Facilities, Craig R. Witt

Dissertations

Background: Women in early recovery from substance use disorder often face metabolic health vulnerabilities, yet physical health behaviors are frequently under-emphasized in sober living settings. Feasible and accessible wellness strategies are needed to support both behavioral and metabolic health in this population.

Purpose: To compare the effects of professionally delivered in-person health coaching versus peer-coordinated virtual health coaching on metabolic outcomes and health-promoting behaviors among women in sober living facilities.

Methods: In this quasi-experimental study, 32 women enrolled in a 12-week group-based health coaching program focused on nutrition, physical activity, and stress management; 18 completed post-intervention assessments (in-person: n = …

Editorial: To Know Or Not To Know: Causes And Evolution Of Lack Of Awareness Of Cognitive Decline In Neurodegenerative Diseases, Volume Ii, Federica Cacciamani, Kristy A. Nielson, Bernard J. Hanseeuw, Geoffroy P. Gagliardi, Patrizia Vannini

Psychology Faculty Research and Publications

Anosognosia, or the lack of awareness of cognitive, behavioral, or functional deficits, represents a critical challenge in the clinical management of neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia. This condition not only impacts patients, caregivers, and healthcare systems (D'Souza et al., 2011; Turró-Garriga et al., 2013) but also raises important questions about its underlying mechanisms and evolution (Hanseeuw et al., 2020; Starkstein, 2014; Vannini et al., 2017). Despite its critical importance, significant gaps remain in our understanding of cognitive self-awareness in neurodegenerative diseases. Building on the momentum of the first edition of To Know or Not to …

Rethinking Behavioral Reassignment In School Systems: A Restorative Model For Holistic Intervention, Gabriel M. Velez, Thomas Durkin, Kristin Haglund, John H. Grych, Julie Novak, Sherri Walker, Emily Goldstein Nolan, Amanda Krzykowski, Janessa Doucette, Drew Deluito, Bridget Schock

Psychology Faculty Research and Publications

Growing evidence over the last few decades has highlighted that punitive approaches in schools perpetuate violence, furthering inequities, deepening issues of safety, and negatively impacting young people’s development. These impacts are particularly felt in under-resourced urban schools situated in contexts of community violence. Partially, in response, an increasing number of schools and school districts are engaging in restorative practices. This trauma-informed, strengths-based framework focuses on relationships, healing, and accountability. This article contributes to the growing literature on the potential of restorative justice to promote equity in urban schools and educational systems by outlining the development and model of a restorative …

An Iterative Shifting Disaggregation Algorithm For Multi-Source, Irregularly Sampled, And Overlapped Time Series, Colin O. Quinn, Ronald H. Brown, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Accurate time series forecasting often requires higher temporal resolution than that provided by available data, such as when daily forecasts are needed from monthly data. Existing temporal disaggregation techniques, which typically handle only single, uniformly sampled time series, have limited applicability in real-world, multi-source scenarios. This paper introduces the Iterative Shifting Disaggregation (ISD) algorithm, designed to process and disaggregate time series derived from sensor-sourced low-frequency measurements, transforming multiple, nonuniformly sampled sensor data streams into a single, coherent high-frequency signal. ISD operates in an iterative, two-phase process: a prediction phase that uses multiple linear regression to generate high-frequency series from low-frequency …

Computer Vision-Based Framework For Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach To Unlocking Financial Insights, Iftakhar Ali Khandokar, Priya Deshpande

Electrical and Computer Engineering Faculty Research and Publications

Information extraction from financial document images is crucial in computer vision and NLP, as financial data often exists in image or PDF format, enabling organizations to analyze and make informed business decisions using OCR advancements. The table contents of financial document images are one of the prominent structures to confine important portions of data of the document and many Deep learning-based methods have been proposed to detect Table regions inside document images. The shortcomings of the current approach are that it is bounded within the detection of the table region and struggles in cases such as handling different layouts and …

Strategic Leadership In Cybersecurity Risk Management: Elevating The Role Of Executive Managers, Lordt Becklines, Omar F. El-Gayar

Research & Publications

As the frequency and sophistication of cyber threats continue to escalate, cybersecurity has evolved from a technical concern to a central pillar of strategic enterprise governance. This TREO Talk presents the findings of a rigorous systematic literature review (SLR) encompassing 69 scholarly publications selected using the PRISMA 2020 framework. The study investigates how executive managers (EMs) influence the success of cybersecurity risk management (CRM) programs and frames their participation as both a requirement and a competitive advantage. Despite global investment in security infrastructure, many organizations remain vulnerable to breaches, largely due to the absence of sustained executive leadership in CRM. …

Integrating Generative Ai Into Knowledge Management Systems For Context-Aware Decision Support, Thad J. Dymkowski, Omar F. El-Gayar

Research & Publications

In complex organizations, traditional Knowledge Management Systems (KMS) and decision support systems (DSS) often struggle with three persistent challenges: capturing and converting tacit knowledge, like employee expertise and contextual insights, into explicit shareable formats; dynamically adapting recommendations and knowledge delivery to rapidly changing organizational contexts, user roles, and project needs; and enabling fast, relevant knowledge retrieval for timely decision-making. These challenges result in knowledge silos, loss of critical expertise, and decision delays. Integrating Generative AI (GenAI) with KMS, and context-aware DSS (CADSS) directly addresses these challenges by automating the collection, extraction, and structuring of tacit knowledge; personalizing insights based on …

Human Cognitive Bias Mitigation Approaches To Fairness Within The Machine Learning Value Chain: A Review And Research Agenda, Stephen Surles, Cherie Noteboom, Omar F. El-Gayar

Research & Publications

This systematic review examines the influence of human cognitive biases on machine learning (ML) systems across the 9 phases of the ML algorithmic value chain. Following the PRISMA guidelines, it synthesizes 19 studies on bias integration and management within ML, highlighting techniques to reduce bias and increase fairness. The review identifies key gaps: the unclear translation of human cognitive biases to ML biases, absence of metrics to measure biases, re-introduction of biases during debiasing, and the critical need for human intervention. These findings prompt several research themes spanning human cognition and algorithmic bias. The theoretical implications are three-fold: extending bias …

Ai-Powered Operations: Navigating Ethics, Automation, And Strategic Innovation In The Digital Era, Lordt Becklines, Omar F. El-Gayar

Research & Publications

Artificial Intelligence (AI) is redefining Operations Management (OM) by transforming how organizations plan, execute, and optimize their core processes. This TREO Talk presents a comprehensive synthesis of AI’s evolution and impact in OM, underscoring its role as a strategic enabler of agility, resilience, and innovation in digitally driven enterprises. Leveraging a Systematic Literature Review (SLR) guided by PRISMA methodology across nine scholarly databases, this research constructs a validated framework that captures the multidimensional role of AI in transforming operational strategies, capabilities, and outcomes across industries. AI's influence spans predictive analytics, robotic process automation, supply chain orchestration, logistics, and real-time quality …

Non-Functional Requirementsand Key Propositionselicitation For An Hdss:A Grounded Theory Approach, Mohammad Tafiqur Rahman, Omar F. El-Gayar

Research & Publications

Deciding humanitarian actions during relief distribution is a crucial and challengingtask.Humanitarian decision-makers (HDM) make manycritical decisions during disaster responses,but they sufferfrom incomplete, irrelevant, and sometimes excessive humanitarian operations-related disaster datain many situations.Hence, for constructive and meaningful support in decision-making, HDMs oftenappreciate computer-basedinformation systems(IS) (i.e. humanitarian decision support systems) that require non-functional requirements (NFRs) for their development. To identify those necessary NFRs, we applied the grounded theory approach to analyze 61 literature-and field-based decision-making parameters reported in the primary author's previous research (Rahman and Majchrzak (2020)). Our analysis resulted in 13 essentialNFRs and four key propositions to guide relief distribution decision-making …

Evaluating Topic Models With Openai Embeddings: A Comparative Analysis On Variable-Length Texts Using Two Datasets, Abdullah Wahbeh, Mohammad Al-Ramahi, Omar F. El-Gayar, Ahmed Elnoshokaty, Tareq Nasralah

Research & Publications

Topic modeling is a crucial unsupervised machine learning technique for identifying themes within unstructured text. This study compares traditional topic modeling methods, like Latent Dirichlet Allocation (LDA), against advanced embedding-based models, specifically BERTopic-OpenAI. The analysis utilizes two distinct datasets: user reviews from the mental health app Replika and the 20newsgroup dataset. For the Replika dataset, both methods identified common themes, but BERTopic-OpenAI uncovered additional nuanced topics, demonstrating its enhanced semantic capabilities. Quantitative evaluation of the 20newsgroup dataset further highlighted BERTopic-OpenAI's advantage through achieving higher topic coherence and diversity than the best-performing LDA model. These results suggest that embedding-based models provide …

A Review Of Reasoning In Artificial Agents Using Large Language Models, Nagraj Naidu, Omar F. El-Gayar

Research & Publications

The increasing sophistication and the use of large language models (LLMs) in artificial agents highlights the need to investigate their reasoning capabilities and limitations. Understanding these aspects is crucial, given the integral role of reasoning in decision-making processes, which are central to a software or embodied agent. This research paper presents a systematic review of the topic. We review the literature by selecting and analyzing highly cited papers using both PRISMA and snowballing. The gathered literature is categorized using a detailed framework of facets and categories. In the results section, we elaborate on our findings and illustrate the mapping through …

Exploring The Interoperability For Information Exchange Between Acute And Post-Acute Care Settings, Madhu Gottumukkala, Cherie Noteboom, Omar F. El-Gayar

Research & Publications

The seamless transfer and assimilation of healthcare data are foundational to delivering holistic, timely, and effective patient care across the healthcare spectrum. However, disparities in Electronic Health Record (EHR) system adoption, especially in long-term and post-acute care (LTPAC) settings, consistently obstruct interoperability. This study explores the factors that impede and facilitate health information exchange in LTPAC environments, focusing on technical and organizational facets. Grounded theory guided our qualitative case study research, involving 35 stakeholder interviews. Key technical findings highlight the need for integrated, reliable data structures, robust infrastructure, and standardized practices. Organizational insights reveal a shift towards integrative, patient-centric strategies …

Latent Subtypes Of Comorbidities In Multiple Sclerosis Patients: Insights From Social Media, Laxmi Manasa Gorugantu, Nevine Nawar, Omar F. El-Gayar

Research & Publications

Multiple Sclerosis is a chronic neurological disease associated with various physical and cognitive impairments. Individuals with MS might also experience medical and psychiatric comorbidities that can exacerbate the severity of the disease and lower their overall well-being. Therefore, it becomes essential to identify these co-occurring health conditions at the early stages to optimize treatment and improve patient outcomes. Consequently, the objective of this study is to explore the commonly occurring comorbidities among MS patients around the globe from social media discourse. Furthermore, it aims to unveil public perceptions, providing insights that might not be captured via clinical research methods. The …

Highlighting Competency Gaps In Health Informatics Education Using Advanced Text-Embedding Models, Omar F. El-Gayar, Abdullah Wahbeh, Mohammad Al-Ramahi, Ahmed Elnoshokaty

Research & Publications

The healthcare sector anticipates substantial growth, with 125,000 job openings by 2026, including 69,000 middle-skilled positions. Despite this growth, data use and integration inefficiencies cost the sector $750 billion annually. Health informatics, an interdisciplinary field blending healthcare, computer, information, and cognitive sciences, can address these challenges through enhanced healthcare management via information technology. However, there is a critical disparity between competencies taught in educational programs and those demanded by the job market. This study examines competencies from job postings on Indeed.com and accredited health informatics programs, comparing them with the Health Information Technology Competencies (HITComp) database. Utilizing advanced text-embedding models, …