Diagnosis Commons^™

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 …

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 …

Recent Advances In Triboelectric Nanogenerators For Biomedical And Cardiovascular Monitoring, Amit Sarode, Jegan Rajendran, Gymama Slaughter

Center for Bioelectronics Publications

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, …

Modern Potentiostat Architectures For Electrochemical Sensing: Design, Integration, And Future Directions, Reagan Aviha, Gymama Slaughter

Center for Bioelectronics Publications

Potentiostats are essential to electrochemical sensing, enabling precise control of electrode potentials and measurement of current responses. As demand grows for portable, wearable, and point-of-care systems, potentiostat design has evolved from benchtop instruments to compact, low-power, and wirelessly connected platforms. This review provides a comprehensive, system-level perspective on modern potentiostat architectures, covering operational principles, analog front-end design, signal generation and acquisition, communication protocols, and software integration. Unlike prior reviews that treat these aspects independently, this work integrates electrochemical theory with electronic design and data communication frameworks. Key components, including operational amplifiers, transimpedance amplifiers, DAC/ADC subsystems, and microcontroller-based control, are examined …

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.

Clinical Subtypes Of Co-Morbid Insomnia And Obstructive Sleep Apnea (Comisa): Results Of A Cluster Analysis, Yuan Shi, Xujun Feng, Fengyi Hao, Yuru Nie, Yihui Zhang, Zhaohua Chen, Siqi Guan, Larry D. Sanford, Michael V. Vitiello, Xiangdong Tang

Department of Pathology & Anatomy Faculty Publications

Background

Variations in the bidirectional relationship between obstructive sleep apnea (OSA) and insomnia in co-morbid insomnia and OSA (COMISA) may form distinct subtypes of COMISA, which have not been previously characterized. This study aims to identify and characterize subtypes of COMISA.

Methods

From a community-recruited COMISA cohort 256 individuals who met diagnosis for COMISA were used to identify subtypes using a two-step clustering methodology. Demographics and multidimension clinical characteristics were collected and compared among obtained subtypes. Logistic models were used to evaluate whether these subtypes were associated with cardiometabolic and mental disorders. A clinical cohort of 1816 COMISA patients was …

Non-Invasive Detection Of Intracranial Pressure, Andrei V. Nesterenko

Honors Undergraduate Theses

Intracranial pressure is a critical metric used when managing tumors, strokes, TBIs, hydrocephalus, and other operative conditions. Traditional methods for continuous ICP monitoring, intraparenchymal catheters, epidural transducers etc., are invasive and carry a high risk of infection. Previous attempts to create accurate, easy to use, and non-invasive ICP monitoring techniques have been unsuccessful. In this study, we investigated the utility of supraorbital and posterior auricular photoplethysmography to monitor changes in ICP during orthostatic tilt and hyperventilation, which increase and decrease ICP respectively.

Through a continuous 5-minute recording on a tilt-table we characterized SOA and PAA waveforms in 12 participants (ages …

Devising A Protocol For Mri Clearance In Patients With Cardiac Implantable Electronic Devices (Cied), Sienna Luk, Alvin Mathew, Darshan Bhatty, Kamran Rizvi

North Texas GME Research Forum 2026

Background: Magnetic Resonance Imaging (MRI) in patients with Cardiac Implantable Electronic Devices (CIEDs) remains a logistical challenge in many clinical settings. At Medical City Denton, the absence of a standardized institutional policy has led to significant inefficiencies, including prolonged hospital stays and increased healthcare costs. The primary objective of this project was to address these barriers by developing a streamlined, evidence-based protocol to improve care coordination and resource utilization for patients with CIEDs requiring diagnostic imaging.

Methods: Launched in 2026, this pilot initiative utilized a multi-stakeholder approach involving hospitalists, EPs, radiology staff, and device representatives. A core component of the …

Esophageal Squamous Cell Carcinoma Incidentally Detected On Barium Swallow: A Case Report, Muhammad Rubeel Akram, Aditya Rao, Muhammad T. Siddique

North Texas GME Research Forum 2026

Background: Esophageal cancer is an aggressive malignancy with a poor prognosis, and has high rates of recurrence despite curative-intent therapy. While endoscopy with biopsy remains the gold standard for diagnosis, non-diagnostic imaging studies are performed when evaluating for dysphagia, and may bring to light underlying pathology, warranting further workup. Surgical resection following neoadjuvant chemoradiation is often performed, but postoperative complications and disease recurrence are important concerns. This case highlights the crucial role of early detection via imaging and the clinical burden associated with esophageal squamous cell carcinoma.

Case Presentation: A 76-year-old female presented with dysphagia and underwent a barium esophagogram, …

Prognostic Value Of Systemic Inflammatory Indices For Predicting Mace In Nstemi Patients Undergoing Pci, Boney Lapsiwala, Aditya Sharma, Usman Khan, Jorim Parmar, Justin Soloman, Veeranna Vibhuti, Mehdi Khalafi

North Texas GME Research Forum 2026

Background: Cardiovascular diseases (CVD) account for nearly one-third of global mortality, with ischemic heart disease caused by a mismatch between myocardial oxygen supply and demand. Despite advances in percutaneous coronary intervention (PCI) and contemporary pharmacotherapy, patients with non–ST-segment elevation myocardial infarction (NSTEMI) continue to experience substantial residual risk for major adverse cardiovascular events (MACE). As traditional risk stratification tools have limited ability to identify high-risk individuals, interest has shifted toward biomarkers reflecting inflammatory pathways central to atherosclerosis and plaque instability. Hematologic inflammatory markers including pan inflammatory value (PIV), systemic immune inflammation index (SII), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) initially …

Handheld Magnet Screening Of External Fixator Components: A Laboratory Assessment Of Gross Ferromagnetism Relevant To Mri Safety, Troy B. Puga, Mckenna W. Box, Lyn D. Ward, John T. Riehl

North Texas GME Research Forum 2026

Introduction Much controversy remains regarding the ability of patients with an external fixator in place to undergo Magnetic Resonance Imaging (MRI). The main concern for radiology departments is that the external fixator system components can lead to adverse events due to interactions of the external fixator and the magnet of the MRI. However, there is no clear evidence to support these claims or theories in the current literature. Yet, MRI’s are denied daily across the country for patients having an external fixator in place. Numerous patients with an external fixator would likely benefit from an MRI to prevent delayed care, …

Positive Efast—Not So Fast, Barry J. Knapp, Mitchell Vallone, Megan Duggins, Matt Jones, Jacob Knapp, Lily Kauffman, Alexander Dornstauder

Department of Emergency Medicine Faculty Publications

[Patient presentation] A 68-year-old man presented via emergency medical services (EMS) with right hip pain following a traumatic fall from his bicycle. On arrival at the emergency department, he was alert and oriented. Physical examination revealed only tenderness over the greater trochanter of the left femur, with no significant pain on passive range of motion of the left hip. Plain radiography demonstrated a left acetabular fracture (Fig 1).

Ensemble Learning For Predicting Periapical Lesions From Dental Radiographs, Fang-Yuan Liao, Ming-Jyun Jian, Abdullah Sarini, Yulianto Jesica, Yen-Kun Lin, Hsun-Yu Huang

Journal of Dental Sciences

Background/purpose: Diagnosing periapical cysts and granulomas using periapical radiographs is challenging due to subtle radiographic differences. This study aimed to develop a machine learning–based diagnostic framework to improve lesion classification through ensemble learning and dentin standardization.

Materials and methods: Five models—Support Vector Classifier (SVC), Nu-SVC, K-Nearest Neighbors (KNN) and Decision Tree—were trained on 144 pre-treatment periapical radiographs (70 cysts and 74 granulomas). Dentin standardization normalized grayscale values to ensure feature consistency. A weighted soft voting strategy was employed to integrate predictions, with model weights derived from individual diagnostic performance. Model performance was evaluated via five-fold cross-validation. Statistical significance among models …

Exploring The Synergy Between Very Large Transformer And Lstm Models For Effective Medical Captioning From Videos To Text: The Impact Of Captioning In Healthcare, R. V. Aswiga, Moin Ahmed Zahir

Data Science Faculty Publications

In today’s rapidly evolving digital landscape, the demand for accurate and contextually relevant subtitles for image and video content, particularly in the medical domain, is increasingly critical. Despite the proliferation of visual data across various platforms, existing captioning systems often struggle due to variations in visual settings, complex temporal relationships, and nuanced semantics. Additionally, challenges such as limited datasets, privacy issues, and specialized annotation requirements make medical image captioning particularly difficult. To tackle these challenges, we investigate cutting-edge deep learning methodologies, specifically Transfer Learning and Transformer models, through a comparative analysis. Specifically, we focus on Transfer Learning through the MedVisionCapturer …

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 …

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

Department of Emergency Medicine Faculty Publications

[Patient presentation]

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

Maxgrnet: A Multi-Axis Vision Transformer With Improved Generalization For Eye Disease Classification Using Explainable Ai With Insertion-Deletion Operations On Fundus Images, Md Mehedi Hasan Santo, Fuyad Hasan Bhoyan, Fuad Ibne Jashim Farhad, Fahmid Al Farid, Sovon Chakraborty, Md Humaion Kabir Mehedi, Jia Uddin, Hezerul Bin Abdul Karim

Computer Science Faculty Publications

Eye diseases, including diabetic retinopathy (DR), glaucoma, and cataracts, represent a major global health concern and can lead to severe visual impairment or blindness if not identified in a timely manner. This study proposes a novel eye disease classification framework based on a multi-axis vision transformer (MaxViT) applied to color fundus images with Explainable Artificial Intelligence (XAI) techniques to enhance model transparency. The proposed architecture integrates transformer-based attention mechanisms with Global Response Normalization (GRN)-based multi-layer perceptron (MLP) layers to capture complex spatial and contextual relationships within fundus images effectively. The model was evaluated on a publicly available eye disease classification …

Standardization Of Neuromuscular Reflex Analysis—Role Of Fine-Tuned Vision-Language Model Consortium And Openai Gpt-Oss Reasoning Llm-Enabled Decision Support System, Eranga Bandara, Ross Gore, Sachin Shetty, Ravi Mukkamala, Christopher K. Rhea, Brittany S. Samulski, Amin Hass, Atmaram Yarlagadda, Shaifali Kaushik, Malith De Silva, Andriy Maznychenko, Inna Sokolowska, Kasun De Zoysa

VMASC Publications

Background/Objectives: Accurate assessment of neuromuscular reflexes, such as the Hoffmann reflex (H-reflex), plays a critical role in sports science, rehabilitation, and clinical neurology. Conventional interpretation of H-reflex electromyography (EMG) waveforms is subject to inter-rater variability and interpretive bias, limiting reliability and standardization. This study aims to develop an automated, interpretable, and robust agentic AI–driven framework for H-reflex waveform analysis. Methods: We propose a fine-tuned Vision–Language Model (VLM) consortium combined with a reasoning Large Language Model (LLM)–enabled decision support system for automated H-reflex interpretation. Multiple VLMs were fine-tuned on curated datasets of H-reflex EMG waveform images annotated with expert clinical observations, …