Investigative Techniques Commons^™

Diagnostic Accuracy Of The Passive Straight Leg Raise Test In Detecting Compression Of The Lower Lumbar Nerve Roots, Hisham Mohamed Hussein, Ehab Kamel, Mohamed Ragab, Ahmed Elerian

Internet Journal of Allied Health Sciences and Practice

Background: Lumbar nerve root compression is a pathological condition that occurs commonly in the low back pain population. Passive straight leg raise (SLR) is a clinical test widely used to confirm this pathological condition. Yet, its diagnostic accuracy needs further investigation. Objective: To assess the sensitivity and specificity of the passive SLR test in detecting compression of the lower lumbar nerve roots using magnetic resonance imaging as a reference standard. Design: This study is a prospective diagnostic-accuracy study. Methods: One hundred-and-twelve participants (82 males and 30 females) met the inclusion criteria and joined the study. Participants were recruited through direct …

Conceptualizing Care Partners' Burden, Stress, And Support For Reintegrating Veterans: A Mixed Methods Study, Nicholas A. Rattray, Mindy Flanagan, Allison Mann, Leah Danson, Ai-Nghia Do, Diana Natividad, Katrina Spontak, Gala True

School of Medicine Faculty Publications

BACKGROUND: People who support Veterans as they transition from their military service into civilian life may be at an increased risk of psychological distress. Existing studies focus primarily on paid family caregivers, but few studies include spouses and informal non-family "care partners." We sought to identify key challenges faced by care partners of Veterans with invisible injuries. METHODS: Semi-structured interviews were conducted with 36 individuals involved in supporting a recently separated US military Veteran enrolled in a 2-year longitudinal study. CPs completed validated measures on perceived stress, caregiving burden, quality of their relationship, life satisfaction, and flourishing. Independent -tests were …

Convolutional Neural Network Based Machine Learning For Ameloglyphics: A Forensic Analysis, Sanjana Shetty, Sowmya Sv, Dominic Augustine, Saiprasad Alva, Mukul Saini

Annual Research Symposium

Convolutional Neural Network based Machine Learning for Ameloglyphics: A Forensic Analysis

Sanjana Shetty, Sowmya SV , Dominic Augustine, Saiprasad Alva, Mukul Saini Author Affiliations: Department of Oral & Maxillofacial Pathology and Oral Microbiology, Faculty of Dental Sciences, MS Ramaiah University of Applied Sciences, MSR Nagar, Bengaluru-560054, Karnataka, India.

Purpose:

Tooth prints, considered to be the hard tissue analogues of finger prints have been studied extensively over the years by manual and in some cases, digital methods. While Artificial intelligence and Machine Learning have witnessed a steady rise in their applications in various fields with promising results, its utility in ameloglyphics …

Utilizing Primary Human Airway Mucociliary Tissue Cultures To Model Ramifications Of Chronic E-Cigarette Usage., Vincent J Manna, Shannon Dwyer, Vanessa Pizutelli, Salvatore J Caradonna

Rowan-Virtua School of Osteopathic Medicine Departmental Research

Electronic cigarettes are battery powered devices that use a vape-liquid to produce a vapor that is inhaled. A consequence of the rise in e-cigarette usage was the 2019 emergence of a vaping-induced respiratory disease denoted as 'e-cigarette or vaping use-associated lung injury' (EVALI). One of the suspected causes of EVALI is Vitamin E Acetate (VEA), which was found to be a diluent in certain illicit vape-pens, whereas nicotine is commonly diluted in equal parts propylene glycol and vegetable glycerin (PG:VG). The prevalent use of e-cigarettes and the emergence of a novel illness has made understanding how e-cigarette vapors affect our …

A Desirable Advancement But Not Without Concern For Black Blood Sequences: Vessel Wall Imaging May Not Be Blindly Done, Subhendra N. Sarkar

Publications and Research

Time of flight (TOF) gradient echo magnetic resonance angiography (MRA) is a bright lumen method that is supposed to be simpler but is not free of challenges. Post-treatment, tricky geometry, Gd build up and high fields pose challenges and practice variation making some special applications of even the well-developed bright blood method questionable in treated AVMs as discussed in a prior editorial (Sarkar Eur Rad, 2023). In this editorial another, perhaps more important (pseudo-steady state for black blood angiography) is discussed. It has been agreed upon that assessment of vessel wall integrity, particularly plaques and other arterial wall diseases is …

Ai-Enhanced Detection Of Clinically Relevant Structural And Functional Anomalies In Mri: Traversing The Landscape Of Conventional To Explainable Approaches, Pegah Khosravi, Saber Mohammadi, Fatemeh Zahiri, Masoud Khodarahmi, Javad Zahiri

Publications and Research

Anomaly detection in medical imaging, particularly within the realm of magnetic resonance imaging (MRI), stands as a vital area of research with far-reaching implications across various medical fields. This review meticulously examines the integration of artificial intelligence (AI) in anomaly detection for MR images, spotlighting its transformative impact on medical diagnostics. We delve into the forefront of AI applications in MRI, exploring advanced machine learning (ML) and deep learning (DL) methodologies that are pivotal in enhancing the precision of diagnostic processes. The review provides a detailed analysis of preprocessing, feature extraction, classification, and segmentation techniques, alongside a comprehensive evaluation of …

Comparing Cognitive Tests And Smartphone-Based Assessment In 2 Us Community-Based Cohorts., Ileana De Anda-Duran, Preeti Sunderaraman, Edward Searls, Shirine Moukaled, Xuanyi Jin, Zachary Popp, Cody Karjadi, Phillip H Hwang, Huitong Ding, Sherral Devine, Ludy C Shih, Spencer Low, Honghuang Lin, Vijaya B Kolachalama, Lydia Bazzano, David J Libon, Rhoda Au

Rowan-Virtua School of Osteopathic Medicine Departmental Research

BACKGROUND: Smartphone-based cognitive assessments have emerged as promising tools, bridging gaps in accessibility and reducing bias in Alzheimer disease and related dementia research. However, their congruence with traditional neuropsychological tests and usefulness in diverse cohorts remain underexplored.

METHODS AND RESULTS: A total of 406 FHS (Framingham Heart Study) and 59 BHS (Bogalusa Heart Study) participants with traditional neuropsychological tests and digital assessments using the Defense Automated Neurocognitive Assessment (DANA) smartphone protocol were included. Regression models investigated associations between DANA task digital measures and a neuropsychological global cognitive

CONCLUSIONS: Our findings demonstrate that smartphone-based cognitive assessments exhibit concurrent validity with a …

Digital Phobia: An Inquiry For Mapping The Unseen Dimension Of New Digital Anxiety, The ‘Digiphobia’, Amarjit Kumar Singh ,Library Assistant, Md. Arshad Ali , Professional Assistant, Dr. Pankaj Mathur, Deputy Librarian,

Library Philosophy and Practice (e-journal)

Background: As technology continues to advance, individuals' interactions with digital platforms have become integral to daily life. Amidst this technological evolution, a novel concern emerges—Digital Phobia, hereafter referred to as “Digiphobia.” This phenomenon, although not previously explored in scholarly literature, necessitates an in-depth investigation due to its potential impact on individuals' well-being. Our research employs a two-step methodology to investigate its existence, implications, and manifestations.

Introduction: This research paper introduces and proposes the term "Digiphobia" as a comprehensive conceptualization of anxiety arising from interactions with digital spaces, applications, and environments. The proliferation of digital technologies has led to the emergence …

Gastric Lipomas: A Case Series And Review Of The Literature, Simone A. Jarrett, Sahana Tito, Matthew Chan, Dominic E. Jarrett, Kevin B. Lo, Richard Depalma

Einstein Health Papers

INTRODUCTION: The purpose of this case series was to review a rare subset of tumors known as gastric lipomas, which are typically found incidentally. The motivation for this study arose from the identification of 2 cases within our institution in a short period.

CASE PRESENTATION: The study involved a review of the diagnosis and management of 2 patients presenting with gastric lipomas at our institution after symptoms of gastrointestinal bleeding. With the advent of new radiologic investigations such as computed tomography and magnetic resonance imaging and advances in endoscopy, there are new approaches to identifying and managing these tumors. On …

Postoperative Systemic Inflammatory Response Syndrome Predicts Increased Mortality In Patients After Elective Craniotomy, Liyuan Peng, Qi Gan, Yangchun Xiao, Jialing He, Xin Cheng, Peng Wang, Lvlin Chen, Tiangui Li, Yan He, Weelic Chong, Yang Hai, Chao You, Fang Fang, Yu Zhang

Department of Medical Oncology Faculty Papers

Introduction: Patients undergoing craniotomy are at high risk of perioperative morbidity and mortality due to excessive inflammatory responses. The purpose of the present study is to evaluate the prognostic utility of postoperative systemic inflammatory response syndrome (SIRS) in patients undergoing craniotomy.

Methods: We performed a retrospective cohort study of patients who underwent craniotomy between January 2011 and March 2021. SIRS was diagnosed based on two or more criteria (hypo-/hyperthermia, tachypnea, leukopenia/leukocytosis, tachycardia). We used univariate and multivariate analysis for the development of SIRS with postoperative 30-day mortality.

Results: Of 12,887 patients who underwent craniotomy, more than half of the patients …

Digital Clock Drawing As An Alzheimer's Disease Susceptibility Biomarker: Associations With Genetic Risk Score And Apoe In Older Adults, L I Thompson, M Cummings, S Emrani, David J. Libon, A Ang, C Karjadi, R Au, C Liu

Rowan-Virtua School of Osteopathic Medicine Departmental Research

BACKGROUND: Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection.

OBJECTIVE: We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker.

DESIGN: We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures.

SETTING: We used existing data …

Mandatory Second Opinion To Reduce Caesarean Section Rate Among Low-Risk Pregnant Women At A Private Tertiary Hospital: An Analysis Using Who Robson Classification., Gregory Ntiyakunze

Master of Obstetrics and Gynecology

v> The caesarean section rate has increased globally, even among low-risk obstetric deliveries. Consequently, mothers and babies are exposed to potential complications associated with caesarean sections. Therefore, the World Health Organization has introduced measures to reduce unnecessary caesarean sections, including a globally accepted classification system for all deliveries Robson's system and recommended safe non-medical interventions, such as mandatory second opinions prior to caesarean sections

Identifying Demographic Disparities In Urine Drug Screen Ordering In Psychiatric Inpatients, Michael Tompkins, Jacob Henderson, Eileen Venable, Jeffrey Ferraro

North Florida Division GME Research Day 2024

No abstract provided.

Advancing School Nursing Practice: A Novel Approach To Screening For Gastrointestinal Disorders In Children, Ashley Bunting, Isabella Cavlan

Nursing | Student Research Posters

California schools currently only screen for vision and hearing, leaving many other health concerns unaddressed. Among these, gastrointestinal (GI) health is particularly significant, as digestive disorders can lead to severe consequences, like malnutrition and stunted growth. By incorporating routine GI screenings, school nurses can promote the early detection of disease, allowing for timely intervention and improved health outcomes in children.

Based on existing literature, we have developed a novel pediatric GI screening tool for school nurses to use in routine screenings, presented below.

Autochthonous Plasmodium Vivax Infections, Florida, Usa, 2023, Swamy Rakesh Adapa, Kami Kim, Liwang Cui

College of Medicine & TGH Faculty Publications

During May–July 2023, a cluster of 7 patients at local hospitals in Florida, USA, received a diagnosis of Plasmodium vivax malaria. Whole-genome sequencing of the organism from 4 patients and phylogenetic analysis with worldwide representative P. vivax genomes indicated probable single parasite introduction from Central/South America.

A Tool To Automate Neuropathological Assessment In Huntington Disease Mouse Models, Samuel A. Moldenhauer

Honors Undergraduate Theses

As our life expectancy continues to rise, so does the prevalence of neurodegenerative diseases, such as Huntington disease (HD). Neurodegeneration leads to progressive regional brain atrophy, typically initiating prior to symptom onset. With the advancements of medical treatments designed to target neurodegeneration, researchers measure their impact on atrophy in animal models to assess their effectiveness. This is important because treatments designed to combat neuropathology are more likely to modify the disease itself, per contra to treatments designed to mask or treat symptoms. One method of brain region size quantification is magnetic resonance imaging (MRI), which while accurate, is prohibitively expensive. …

Assessment Of Forensic And Clinical Criteria Of Orbital Blowout Fractures For Use In Bioarchaeological Analysis, Dylan E. Ornot

Honors Undergraduate Theses

Orbital blowout fractures are a particular facial fracture occurring within the inner eye orbits of the face caused by blunt force trauma to the eyeball or the lower orbital rim. This fracture is common in modern clinical contexts due to physical assaults, but examining this fracture in skeletal material can also provide insights into the patterns of interpersonal violence within the fields of bioarchaeology and forensic anthropology. Issues with analyzing this fracture in skeletal material arise due to the clinical assessment practices of blowout fractures, where medical practitioners are highly focused on the soft tissue presentations of the fracture in …

Utilizing Ai Integrated Neuroimaging Technology To Expand Upon Machine Learning In Positron Emission Tomography Technology With The Aim Of Detecting Amyloid Beta Biomarkers Early In The Onset Of Alzheimer's., Ethan S. Terman

UROP Posters

Early intervention in Alzheimer's is vital for treatment. The earlier a professional can detect symptoms and make a diagnosis the earlier a prognosis can be implemented. With the prevalence of data in our day-to-day world combined with Artificial intelligence (AI), utilizing both for machine learning can pave the way for more accurate and efficient detection of Alzheimer's and other neurodegenerative diseases. AI combined with Machine learning (ML) increases diagnostic efficiency and reduces human errors, making it a valuable resource for physicians and clinicians alike. With the increasing amount of data processing and image interpretation required, the ability to use AI …

Integrated Machine Learning And Deep Learning Models For Cardiovascular Disease Risk Prediction: A Comprehensive Comparative Study, Shadman Mahmood Khan Pathan, Sakan Binte Imran

Electrical & Computer Engineering Faculty Publications

Cardiovascular Diseases (CVDs) pose a significant global health challenge, necessitating accurate risk prediction for effective preventive measures. This comprehensive comparative study explores the performance of traditional Machine Learning (ML) and Deep Learning (DL) models in predicting CVD risk, utilizing a meticulously curated dataset derived from health records. Rigorous preprocessing, including normalization and outlier removal, enhances model robustness. Diverse ML models (Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbor, Decision Tree, and Gradient Boosting) are compared with a Long Short-Term Memory (LSTM) neural network for DL. Evaluation metrics include accuracy, ROC AUC, computation time, and memory usage. Results identify the …

Taste And Learning In The Gustatory Cortex, Martin Raymond

Alternative Theses and Dissertations (AETDs)

This research investigates the organization of taste representations in the gustatory cortex (GC) through two experiments utilizing miniscope imaging in mice. The first experiment focuses on conditioned taste aversion (CTA) and reveals that taste representations in GC are heavily dominated by palatability, with shifts in representational space occurring as a function of learning and extinction. The second experiment explores the interrelation of aversive stimuli, the impact of novelty on taste representations, and the role of somatosensory feedback. Findings suggest that familiarity and palatability emerge as positive signals with experience, shaping taste representations in GC. The study contributes to a nuanced …