Diagnosis Commons^™

The Role Of Extracellular Vesicles As Diagnostic Tools In Gut-Brain Axis Disorders, Patricia Marçal Da Costa, Paulo Iury Gomes Nunes, Gabriella Cunha Vieira Ciurleo, José Wagner Leonel Tavares Junior, Pedro Braga Neto, Ludmila Belayev, Reinaldo Barreto Oriá

School of Graduate Studies Faculty Publications

The gut–brain axis represents a dynamic two-way signaling network whose dysregulation has been implicated in a wide range of neurogastrointestinal disorders. In this context, extracellular vesicles (EVs) have emerged as critical mediators of intercellular signaling and as promising non-invasive biomarkers. Derived from host and microbial cells, EVs carry bioactive cargo—including proteins, lipids, nucleic acids, and metabolites—that reflect the physiological or pathological state of their cells of origin. Their ability to cross biological barriers, such as the blood–brain barrier, underscores their potential for diagnosing and monitoring gut–brain axis dysfunctions. In this mini-review, we integrate microbial and brain-derived EVs within the framework …

Seconds Matter: Rapid Pocus Diagnosis Of Ruptured Type B Aortic Dissection With Left Hemothorax, Jeby Kalathoor, Derrick Huang

Gulf Coast Division GME Research Day 2026

No abstract provided.

Beware Of Bears: Severe Hydronephrosis & Urinary Retention Hidden Behind A Uti, Bjorn Sorensen, Victoria Jackson, Carissa Ford

Gulf Coast Division GME Research Day 2026

No abstract provided.

Tackling Tele Box Shortage Via Educational Initiative, Guntash Khasria, Bushra Ambreen

Gulf Coast Division GME Research Day 2026

No abstract provided.

Partial Molar Pregnancy With Extreme Elevation Of Quantitative Β-Hcg, Zachary Franklin, Amanda Royek, Kaitlyn Vu, Anthony Royek

South Atlantic Division GME Research Days 2026

No abstract provided.

Wearable Biosensors For Continuous Monitoring Of Chronic Kidney Disease: Materials, Biofluids, And Digital Health Integration, Anupamaa Sivasubramanian, Shankara Narayanan, Gymama Slaughter

Center for Bioelectronics Publications

Chronic kidney disease (CKD) is a progressive and irreversible disorder affecting over 850 million individuals globally and is associated with significant morbidity, mortality, and healthcare burden. Conventional diagnostic approaches rely on intermittent laboratory measurements, including serum creatinine, estimated glomerular filtration rate (eGFR), and urinary albumin, which provide limited temporal resolution and fail to capture dynamic physiological changes. Recent advances in wearable biosensing technologies offer new opportunities for continuous, non-invasive monitoring of biochemical and physiological markers relevant to renal function. This review provides a comprehensive analysis of wearable biosensors for CKD monitoring, focusing on sensing mechanisms (electrochemical, optical, and field-effect transistor), …

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. …

Acute Aortic Dissection Masquerading As Testicular Torsion: A Case Report, Bruce M. Lo, Megyn K. Christensen, Coral E. Byrns, Benjamin Chidester

Department of Emergency Medicine Faculty Publications

Introduction: Aortic dissection is a rare but life-threatening condition with a high mortality rate if diagnosis is delayed. Aortic dissection classically presents with sudden-onset, sharp pain in the chest or back. However, atypical presentations can also occur, which could lead to a delay in diagnosis.

Case Report: A patient initially presented to the emergency department (ED) with left testicular pain ongoing for several hours. On examination, he had tenderness in the left lower quadrant abdomen and left testicle. A testicular ultrasound revealed decreased blood flow to the left testicle, raising concern for testicular torsion. The patient was taken to the …

Minimizing Unnecessary Ttes For Pfo Evaluation In Stroke Patients, Jeffrey Lesser, Salman Islam, Aneesha Shaju, Aarohi Parikh, Jonathan Nguyen, Marelle Montanez

Gulf Coast Division GME Research Day 2026

No abstract provided.

Mechanical-Medical Convergence In Heart Failure: Artificial Intelligence, Finite-Element Modeling, And 3d Printing For Diagnosis And Prognosis, Quazi Noor E. Sabrina, Quazi Md Zobaer Shah, Quazi Noor E. Sohela, Md Mahabub Hasan Mousum, Md. Moyeen Uddin Chisty, Quazi Md. Akbar Shah

Mechanical & Aerospace Engineering Faculty Publications

Heart failure remains a leading cause of global morbidity and mortality, yet routine clinical indices often miss the regional biomechanical disturbances that drive progression and shape treatment response. This State-of-the-Art review examines how finite-element (FE) modeling, additive manufacturing, and artificial intelligence (AI) are converging to improve the diagnosis, phenotyping, procedural planning, and prognostic assessment of heart failure (HF). Although these technologies have matured in structural heart disease and transcatheter intervention research, their greatest translational potential may lie in HF, where patient-specific ventricular remodeling, myocardial stress–strain heterogeneity, valve-ventricular coupling, and device-tissue interaction are incompletely captured by conventional clinical indices. We synthesize …

Accuracy Of Estimated Fetal Weights As You Progress Through Residency, Madison Pearson, Lauren Robertson, Emily Coughlin, James Baron, Mark Sanchez

West Florida Division GME Research Day 2026

No abstract provided.

Incidence Of False-Positive Tubal Occlusion On Hysterosalpingography (Hsg) Due To Tubal Spasm: A Case Series, Elena Korytnikova, Ben Duplaga, Mark Sanchez

West Florida Division GME Research Day 2026

No abstract provided.

A New Conceptual Framework For The Approach To The Emergency Department Patient, Christopher Houston

North Texas GME Research Forum 2026

Background

The Emergency Department (ED) is an often chaotic environment where you have little information, little time, and must evaluate for multiple serious conditions. This can be overwhelming for trainees and young physicians. Having a thought process specifically tailored to the ED could be helpful organizing priorities and diagnostic pathways. There are several disease specific core measures that are time sensitive in the ED. Specifically; STEMI, stroke, sepsis, and trauma. Each of these conditions must be rapidly identified, and appropriate pathways initiated.

Trainees are traditionally taught to approach a patient with a wide differential diagnosis for each chief complaint and …

Improving Cord Gas Collection Rates On Labor & Delivery, Sandra Zhi, Diane Gilbertson, Ifeoluwa Adesina-Aina, Sarah Moore, Jack Graham

North Texas GME Research Forum 2026

Background: Cord blood gas measurements are helpful to determine the acid-base status of a neonate after delivery and can determine risk for neonatal encephalopathy. Collection usually occurs right after delivery of the infant and after the umbilical cord has been cut and clamped. The OBGYN residents are currently trained to draw cord blood for gas analysis if clinical status of the neonate is subpar, but there exist other indications for drawing cord blood to send for cord gases as recommended by the American College of Obstetricians and Gynecologists as well as the American Academy of Pediatrics. This project will focus …

Operative Localization Of Occult Gastrointestinal Bleeding Using Intraoperative Small Bowel Endoscopy, Shuda Xia, Furrukh Jabbar, Muhammad T. Siddique

North Texas GME Research Forum 2026

No abstract provided.

A Practical Phenotyping Framework For Male Lower Urinary Tract Symptoms Using Remote Multi-Day Urinary Diagnostics, Jeremy Watts, Daniel Godelfer, John Knoedler, Ashley Sturdy, Steven Kaplan, Ilya Sobol

Department of Urology Faculty Publications

Objective

To describe the distribution of predefined Index Symptoms and Diagnostic Profiles in a cohort of men undergoing Remote multi-day urinary diagnostics (RMUD) for lower urinary tract symptoms (LUTS).

Methods

We retrospectively analyzed 1,047 RMUD performed with CarePath® in men referred for LUTS across 18 sites. RMUD combined multi-day frequency-volume and uroflowmetry data with the IPSS. Six Index Symptoms were operationalized: (1) low flow with elevated IPSS (device trial criteria), (2) overactivity, (3) primary overactivity (overactivity without obstructive RMUD findings), (4) nocturia, (5) nocturnal polyuria (NP) using the ICS NP index, and 6) no qualifying voids. Combinations of the Index …

Improving Medical Diagnostics With Vision-Language Models: Convex Hull-Based Uncertainty Analysis, Ferhat Ozgur Catak, Murat Kuzlu, Taylor Patrick, Michel Audette

Engineering Technology Faculty Publications

In recent years, vision-language models (VLMs) have been applied to various fields, including healthcare, education, finance, and manufacturing, with remarkable performance. However, concerns remain regarding VLMs' consistency and uncertainty, particularly in critical applications such as healthcare, which demand a high level of trust and reliability. This paper proposes a novel approach to evaluate uncertainty in VLMs' responses using a convex hull approach on a healthcare application for visual question answering (VQA). For any VLM, temperature refers to a sampling parameter used in probabilistic generation, which controls the randomness of the model's output. The LLM-CXR model is selected as the medical …

Advances And Challenges In Digitally Connected Point-Of-Care Biosensing, Abdellatif Ait Lahcen, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Point-of-care (POC) biosensors are undergoing a paradigm shift from isolated diagnostic tools to digitally connected, intelligent platforms that enable continuous and decentralized healthcare delivery. This review critically examines recent advances in wearable, implantable, and portable biosensors, highlighting how integration with wireless communication, the Internet of Medical Things (IoMT), and artificial intelligence is transforming their functionality and clinical utility. Particular attention is given to innovations such as smartphone-enabled interfaces, cloud-based analytics, and machine learning-assisted analysis, which collectively enhance sensitivity, specificity, and user accessibility across diverse healthcare settings, from personalized home monitoring and bedside diagnostics to deployment in resource-limited regions. The review …

Rapid Diagnosis Of Hemorrhagic Shock Due To Upper Gi Bleeding With Point-Of-Care Ultrasound In The Emergency Department, Tamari Ronen, Derrick Huang

Gulf Coast Division GME Research Day 2026

No abstract provided.

Training Set Augmentation And Biology-Aware Harmonization Improve Radiomic Models For Lung Cancer Prediction In Indeterminate Nodules, Claire Huchthausen, Menglin Shi, Gabriel De Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

CT radiomics-based machine learning has potential to predict lung cancer in pulmonary nodules (PNs) earlier than standard-of-care methods. Low malignancy rates in early-development PNs and variable image acquisition hinder development of radiomic models for diagnosing these PNs. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We examine early-development benign and malignant PNs (n = 106) below the sensitivity of standard-of-care diagnosis. Classifiers predicting malignancy performed near chance when trained on ComBat-harmonized radiomic features from only early-development PNs. We then augmented training with later-development benign and malignant PNs (n = 225). We evaluated whether …