Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Advocateai: A Human-In-The-Loop Artificial Intelligence Platform To Improve Diagnostic Trajectories And Patient Empowerment In Chronic Pelvic Pain, Gayatri Bhanot, Ashley Kochans

InnovateHER Meeting 2026

Chronic pelvic pain (CPP) affects up to 27% of women globally^1, yet diagnosis takes 4 – 12 years on average² — a crisis driven by healthcare fragmentation, systemic gender bias, and a 62% rate of symptom dismissal by healthcare providers³. AdvocateAI is a human-in-the-loop AI platform designed to empower patients to accelerate their own diagnostic journey. By synthesizing fragmented medical records and patient-reported symptoms, the tool creates structured clinical summaries and personalized advocacy scripts. Here, we present our findings from discovery, including a landscape analysis of available CPP treatments, a prototype co-designed by patients, and custom …

Endometriosis Knowledge Among Emergency Medicine Providers: Diagnostic Skills And Symptom Recognition, Caidon Iwuagwu, Laurel X. Chen, Ellen Slattery, Pranjal Srivastava, Hamsitha Karra, Sheyenne Tung, Adrienne Burton, Camila Bomtempo, Jamie Aranda

Department of Surgery Faculty Papers

Objective: Endometriosis is associated with significant diagnostic delays, averaging 6.7 years, largely due to nonspecific symptoms and inadequate diagnostic approaches. Over 15,000 emergency department (ED) visits in the United States annually involve patients with endometriosis, highlighting the need for knowledge of endometriosis. This study surveys emergency medicine (EM) attendings, residents, nurse practitioners, physician assistants, and fellows to assess knowledge and practice in managing endometriosis-related ED complaints. Methods: A questionnaire from a prior endometriosis survey was modified for EM providers and administered anonymously via email (Qualtrics, Provo, UT) in monthly newsletters to providers at an academic and six associated community EDs. …

An Ai Approach To Differentiating Lung Squamous Cell Carcinoma From Metastases Of Other Origins, Mark G Evans, Jennifer Ribeiro, Todd Maney, Anthony Helmstetter, Jennifer Johnson, Anthony Karnezis, Casey Bales, George Sledge, David Spetzler, Ari Vanderwalde, Matthew Oberley, Balazs Halmos, Hossein Borghaei, Farah Abdulla, David Bryant, Fred Hirsch, Hassan Ghani

Department of Medical Oncology Faculty Papers

IMPORTANCE: Distinguishing primary lung squamous cell carcinoma (SCC) from squamous metastases to the lung is a clinical challenge due to histopathologic similarities. Accurate diagnosis is essential to guide treatment decisions.

OBJECTIVE: To assess the utility of an artificial intelligence (AI) approach that includes evaluation of key orthogonal evidence in distinguishing primary lung SCCs from metastatic tumors of other tissue origins.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used GPSai, a tissue-of-origin AI model run automatically on each sample submitted for molecular profiling, to flag potential misdiagnoses among research-eligible cases submitted as lung SCC. Molecularly profiled cases within the Caris Life …

Accuracy Of Frozen Section For Hpv-Associated Squamous Cell Carcinoma Of Unknown Primary, Sindhura Sridhar, Annie Moroco, Shravan Gowrishankar, Mitra Mehrad, Kim Ely, James Lewis, Madalina Tuluc, Stacey Gargano, Melanie Hicks, Kyle Mannion, Arielle Thal, Adam Luginbuhl, Joseph Curry, David Cognetti, Michael Topf

Department of Otolaryngology - Head and Neck Surgery Faculty Papers

INTRODUCTION: Current guidelines for the management of metastatic squamous cell carcinoma of unknown primary (SCCUP) recommend submission of suspicious primary sites for frozen section analysis (FSA). This study aims to investigate the diagnostic accuracy of FSA for identification of HPV-associated SCCUP.

METHODS: A retrospective cohort study of patients with biopsy-proven p16-positive SCCUP who underwent diagnostic operation at two tertiary care institutions was performed. Sensitivity, specificity, PPV, and NPV of diagnostic FSA were assessed.

RESULTS: 77 patients were included in analysis. 66 patients underwent definitive TORS (diagnostic TORS operation with subsequent neck dissection after identification of the occult primary tumor), 7 …

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 …

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 …

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 Fishy Situation: Hand Infection Due To Mycobacterium Marinum Mistaken For Giant Cell Tumor, Alynna Knaub, Dylan Baker, Jennifer Hanrahan

Department of Medicine Faculty Publications

Mycobacterium marinum is an acid-fast bacterium (AFB) associated with exposure to water and aquatic species. When inoculated, infection can result in nodular cutaneous lesions. In the absence of detailed history or culture data, these nodular skin lesions can be mistaken for noninfectious orthopedic conditions. We present a case of M. marinum mistaken for a giant cell tumor. This case illustrates the overlap in these conditions, as well as the utility of QuantiFERON Gold testing to provide supportive evidence for the diagnosis of Mycobacterium marinum.

Diagnosis Of Platelet Dysfunction In Children: Clinical Predictors And Test Methods, Bhavya S. Doshi, Eric N. Thompson, Walter Faig, Abigail Wax, Amrom E. Obstfeld, Michele P. Lambert

Student Papers, Posters & Projects

Evaluation for platelet function disorders (PFD) in children is complicated by their limited exposure to hemostatic challenges, large volumes needed for light transmission aggregometry (LTA) testing, and limited data on the performance characteristics of whole-blood methods such as whole-blood impedance lumiaggregometry (WBILA). The objective of this study was to determine the clinical variables associated with the diagnosis of a PFD. A single-center, retrospective, cohort study of children evaluated for PFD was conducted. Medical charts were abstracted for demographics, medications, testing indications, bleeding sites and severity, and laboratory results. Univariate odds ratios (OR) and multivariable modeling were conducted for association of …

Inflammation And Detection: Rethinking The Biomarker Landscape In Gastric Cancer, Keykavous Parang, Koosha Paydary

Pharmacy Faculty Articles and Research

Gastric carcinoma is a leading cause of cancer-related mortality worldwide, yet reliable noninvasive biomarkers for its early detection remain limited. As research continues to elucidate the inflammatory underpinnings of tumor initiation and progression, it has become increasingly clear that pro-inflammatory cytokines may hold promise as diagnostic adjuncts. Serum cytokines such as interleukin (IL)-1β, IL-6, IL-8, and interferon-gamma have been frequently reported as elevated in gastric cancer patients compared to healthy individuals. These molecules, known for their roles in modulating tumor-promoting inflammation, angiogenesis, and immune evasion, may serve as accessible indicators of disease presence or progression. Several studies have shown that …

Artificial Intelligence In The Management Of Leukemia, Stephanie Koo, Austin P. Runde, Melvin Speisman

School of Medicine

BACKGROUND: Recently, given the demonstrated ability of AI to accurately characterize complex pathologies, AI has been proposed to be of use in the diagnosis, treatment, and monitoring of leukemias given their genetic complexity and subtype heterogeneity, array of treatments, and need for relapse detection. AI has several potential applications in the management of leukemia. First, it can be used to detect leukemia; using AI to detect nuances in lab values can ensure these deadly cancers are never missed. Second, AI can be used to risk-stratify patients and personalize treatments; leukemias are among the most genetically complex cancers with well-characterized risk …

Biofluid Biomarkers Aid In Diagnosing And Developing Improved Treatments For People With Alzheimer's Disease, Jonatan A. Lopez

University Honors Theses

Dementia is a disease in which daily life is disrupted by a loss of cognitive function. Late-onset Alzheimer's disease (AD) is the most common dementia that largely begins to affect individuals in their mid 60s or older. AD was selected as the focus of this paper because it is the most common form of dementia, accounting for 50-70% of dementia cases. A typical diagnostic approach used by physicians starts with a simple clinical test, the Mini-Mental State Examination (MMSE), when cognitive decline is suspected in a patient. Then if there is enough evidence to suggest AD, a physician would order …

Sustained Impact: Long-Term Application Of Diagnostic Uncertainty Communication Training, Danielle M. Mccarthy, Jethel Hernandez, Dimitrios Papanagnou, Kenzie A. Cameron, David H, Salzman, Andrew W. Long, Alexandra D. Franiek, Kristin L. Rising

Department of Emergency Medicine Faculty Papers

OBJECTIVES: More than one-third of discharged emergency department (ED) patients leave without a clear diagnosis for their symptoms. In 2019-2020, we implemented a simulation-based mastery learning curriculum across two academic medical centers to train emergency medicine residents to discuss diagnostic uncertainty during ED discharge, guided by the Uncertainty Communication Checklist (UCC). We sought to assess if this cohort continues to apply skills learned and to obtain trainee insights into the most valuable checklist items.

METHODS: A survey was emailed to all 109 participants who completed the training in 2019-2020. Questions assessed how often participants currently encountered uncertainty and used the …

Schistosoma Haematobium Infection In Ethiopian Children: Evaluating Praziquantel Efficacy, Nutritional Effects, And Diagnosis Using Flukecatcher, Louis Fok

Theses & Dissertations

Urogenital schistosomiasis continues to impact the wellbeing of hundreds of millions of people worldwide and remains a significant public health challenge across Ethiopia. Despite existing knowledge on the disease, there remain significant unanswered questions with regard to its treatment and diagnosis. This dissertation evaluated the efficacy of praziquantel at treating urogenital schistosomiasis, improving nutritional parameters among children and the performance of FlukeCatcher at detecting and determining the intensity of infection. In effecting this, a total of 977 children aged 5 through 15 from the Afar and Gambella regions of Ethiopia were screened for S. haematobium infection using urine filtration microscopy …

Case Report: A Case Of Transient Dress Syndrome (Drug Rash With Eosinophilia And Systemic Symptoms), Dip Patel, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

We report a case of a 41-year-old female with a history of hypertension who presented with fever and a diffuse erythematous rash after taking trimethoprim-sulfamethoxazole (TMP-SMX) for an ear infection. Due to her symptoms, mild eosinophilia, and elevated liver function tests, Drug Reaction with Eosinophilia and Systemic Symptoms (DRESS) was suspected. Although the patient’s rash had resolved by the time of initial evaluation, it recurred overnight, reinforcing suspicion for DRESS syndrome. TMP-SMX was discontinued, and acetylcysteine was administered due to the patient’s high-dose use of acetaminophen in the days prior to her hospital presentation. Infectious and autoimmune workups were negative. …

Case Report: Cold Urticaria Diagnosed In The Emergency Department, Philip Carhart, James Espinosa, Alan Lucerna

Rowan-Virtua Research Day

Cold urticaria can be primary (idiopathic) or can be due to underlying hematologic or infectious diseases. Here we present the case of a young female patient with no past medical history who was diagnosed with cold urticaria in the emergency department setting, using a cold stimulation test. Most cases are idiopathic. The reaction can be triggered in individual cases by exposure to cold objects or to generalized cold ambient temperatures, as was the case in the patient presented here. The physical response is most commonly pruritic wheals (urticaria). However, more severe symptoms may occur up to angioedema with hoarseness and …

Evaluating A Large Language Model’S Accuracy In Chest X-Ray Interpretation For Acute Thoracic Conditions, Adam M. Ostrovsky

SKMC Student Presentations and Publications

BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologist availability can impact clinical decision-making. AI models, including deep learning algorithms, have been explored for diagnostic support, but the potential of large language models (LLMs) in emergency radiology remains largely unexamined.

METHODS: This study assessed ChatGPT's feasibility in interpreting chest X-rays for acute thoracic conditions commonly encountered in the ED. A subset of 1400 images from the NIH Chest X-ray dataset was analyzed, representing seven pathology …

Four Overlooked Errors In Roc Analysis: How To Prevent And Avoid, Zhuoqiao He, Qingying Zhang, Manshu Song, Xuerui Tan, Wei Wang

Research outputs 2022 to 2026

Diagnostic tests are frequently applied within clinical practice to assist with disease diagnosis, differential diagnosis, disease grading and prognosis evaluation. Receiver operating characteristic (ROC) curve analysis is one common approach for analysing discriminative performance of a diagnostic test, where it can determine the optimal cut-off value with the best diagnostic performance.1 However, as a majority of clinicians are non-statisticians, several errors have been observed in clinical research when applying ROC curves. These errors may be misleading in the selection of diagnostic tests and disease diagnosis, thus adding to patient burden. To address these errors, clinicians do not need a …

Can Residents Cheat The Unknown Slide Sessions By Using The Large Language Models? Which Model Should They Use: Chat-Gpt, Claude, Or Gemini?​, Gul Emek Wymer, Susana Ferra

East Florida Division GME Research Day 2025

Introduction: In recent years, artificial intelligence tools, such as large language models (LLMs) have expanded the potential for diagnostic medicine, including histopathology. This study aims to evaluate the diagnostic ability and utility of the publicly available large language models in predicting the accurate diagnosis of the unknown cases by using the images of the hematoxylin-eosin stained slides taken by a mobile phone and compare their performance with the residents’ performance.

Method: The twenty cases, including a variety of entities, were collected from teaching sets of non-HCA patients and public available domains, which are used for unknown slide sessions for residents. …

Postpartum Depression In Adolescent Mothers: Evaluating The Effectiveness Of Screening Tools, Social And Cultural Interventions, Ysabella M. Co

Nursing | Senior Theses

Background: Pregnancies among adolescents is often an outcome of improper sex education and understanding. It is vital to provide mothers with the proper medical care and resources throughout their pregnancy and postpartum period to prevent any risks or harm from occurring. With the complexities and stressors of pregnancy at such a young age, it is important for healthcare to provide resources regarding postnatal depression diagnoses and interventions, especially to a population that is at risk for mental health issues. Objective: To provide adolescent mothers thorough medical care and lessen the risk of experiencing postpartum depression. By providing frequent …

Training Set Augmentation And Harmonization Enables Radiomic Models To Detect Early Onset Of Lung Cancer, Claire Huchthausen, Menglin Shi, Gabriel L.A. Sousa, James Larner, Einsley Janowski, Jonathan Colen, Krishni Wijesooriya

Data Science Faculty Publications

Radiomics-based machine learning models have the potential to detect lung cancer at inception from CT scans and transform patient outcomes. Low malignancy rates in early-development pulmonary nodules (PNs) and variable image acquisition hinder development of clinically applicable radiomics-based early detection models. To address these challenges, we augmented training using later-development PNs and harmonized for acquisition effects. We first trained machine learning models to predict PN malignancy using radiomic features from scans of early-development benign and malignant PNs (n = 187) harmonized using ComBat. Observing near-chance performance, we augmented training with later-development benign and malignant PNs (n = 225). We evaluated …

Molecular Imprinting And Nanomaterial Synergy For Lactate Detection, Christopher Animashaun, Gymama Slaughter

Center for Bioelectronics Publications

Molecularly imprinted polymer (MIP)-based electrochemical sensors have emerged as promising non-enzymatic platforms for the selective and stable detection of clinically and environmentally relevant biomarkers. This review provides a critical, comprehensive analysis of recent advances in MIP-based lactate sensing, with particular emphasis on hybrid systems that integrate conductive nanomaterials including gold and silver nanoparticles, laser-induced graphene, and reduced graphene oxide. These synergistic combinations leverage enhanced surface area, electrical conductivity, and molecular recognition to improve sensor sensitivity, selectivity, and long-term operational stability. Key fabrication strategies, such as electropolymerization, green nanomaterial synthesis, and surface imprinting, are critically examined for their roles in optimizing …

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.

Anaplastic Large Cell Lymphoma In Children And Adolescents, Eric J. Lowe, Wilhelm Woessmann

Department of Pediatrics Faculty Publications

Anaplastic lymphoma kinase (ALK)-positive anaplastic large-cell lymphoma (ALCL) accounts for >95% of ALCL cases in children and adolescents. The first description of ALCL as a CD30-positive lymphoma in 1985 was followed by the detection of chromosomal translocations involving the ALK gene at chromosome 2p23. The pathogenesis of ALK-positive ALCL is based on signalling from the constitutive active ALK kinase. The clinical characteristics, therapy regimens and outcome data were reported in the 1990s and 2000s. Different chemotherapy regimens led to astonishingly similar long-term event-free survival rates of 70%, independent of the drugs, doses and duration of therapy. Additionally, patients with relapsed …

Educational Case: Bullous Pemphigoid, Ryan C. Saal, Alice A. Roberts, Richard M. Conran

Department of Medicine Faculty Publications

The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see https://www.academicpathologyjournal.org/pcme.1

Optiselect And Enshap: Integrating Machine Learning And Game Theory For Ischemic Stroke Prediction, Pritam Chakraborty, Anjan Bandyopadhyay, Sricheta Parul, Sujata Swain, Partha Sarathy Banerjee, Tapas Si, Hong Qin, Saurav Mallik

Computer Science Faculty Publications

Stroke analysis using game theory and machine learning techniques. The study investigates the use of the Shapley value in predictive ischemic brain stroke analysis. Initially, preference algorithms identify the most important features in various machine learning models, including logistic regression, K-nearest neighbor, decision tree, support vector machine (linear kernel), support vector machine ( RBF kernel), neural networks, etc. For each sample, the top 3, 4, and 5 features are evaluated and selected to evaluate their performance. The Shapley value method was used to rank the models using their best four features based on their predictive capabilities. As a result, better-performing …

Feasibility Of Large Language Models For Ceus Li-Rads Categorization Of Small Liver Nodules In Patients At Risk For Hepatocellular Carcinoma, Jiayan Huang, Rui Yang, Xiaotong Huang, Keyu Zeng, Yan Liu, Jun Luo, Andrej Lyshchik, Qiang Lu

Department of Radiology Faculty Papers

BACKGROUND: Large language models (LLMs) offer opportunities to enhance radiological applications, but their performance in handling complex tasks remains insufficiently investigated.

PURPOSE: To evaluate the performance of LLMs integrated with Contrast-enhanced Ultrasound Liver Imaging Reporting and Data System (CEUS LI-RADS) in diagnosing small (≤20mm) hepatocellular carcinoma (sHCC) in high-risk patients.

MATERIALS AND METHODS: From November 2014 to December 2023, high-risk HCC patients with untreated small (≤20mm) focal liver lesions (sFLLs), were included in this retrospective study. ChatGPT-4.0, ChatGPT-4o, ChatGPT-4o mini, and Google Gemini were integrated with imaging features from structured CEUS LI-RADS reports to assess their diagnostic performance for sHCC. …

The Accuracy Of Detection And Diagnosis Of Oral Lesions By Clinical Dental Students, Carinna Tirtania, Dewi Priandini, Najla Nadiah, Indrayadi Gunardi, Hrishikesh Sathyamoorthy

Journal of Dentistry Indonesia

Objective: To determine the accuracy of diagnosing oral lesions through clinical photos taken by clinical dental students (CDS). Methods: The observational analytic study was conducted on 100 CDS to evaluate 140 clinical photos of oral lesions. The gold standard was evaluated by three oral medicine specialists. Data analysis will be performed using accuracy and kappa tests. Results: The accuracy rate of lesion detection in CDS is high (88.55%) with substantial agreement (κ = 0.66). However, the accuracy rate of diagnosis is low (38.21%) with no agreement (κ = -0.30). Participation in the clinical Oral Medicine module positively …

Medicare To Veterans Affairs Cost Shifting-A Challenging Conundrum, Kenneth W. Kizer, Said A. Ibrahim

JeffMD Academic Affairs

No abstract provided.

Pneumocephalus – Epidural Injection Nightmare, Mohammad A. Rattu, Frank A. Wheeler

Rowan-Virtua Research Day

Pneumocephalus (pneumatocele or intracranial aerocele) is defined as the presence of air in the intracranial space and most commonly occurs after a traumatic event (most commonly head or facial injury), epidural injection, cranial surgery, However, it may also be spontaneous. Classified into simple and tension types, the presentation varies based on severity and progression. Pneumocephalus with onset less than 72 hours prior to presentation is defined as acute, in contrast to a delayed presentation greater than the given timeframe. Symptoms vary based on the amount of air that is present as well as the exact location within the cranial cavity. …