Digital Commons Network^™

A Novel Sensitivity Maximization At A Given Specificity Method For Binary Classifications, Seyyed Mahmood Ghasemi, Chunhui Gu, Johannes F Fahrmann, Samir Hanash, Kim-Anh Do, James P Long, Ehsan Irajizad

Faculty, Staff and Student Publications

In the cancer early detection field, logistic regression (LR) is a frequently used approach to establish a combination rule that differentiates cancer from noncancer. However, the application of LR relies on a maximum likelihood approach, which may not yield optimal combination rules for maximizing sensitivity at a clinically desirable specificity and vice versa. In this article, we have developed an improved regression framework, sensitivity maximization at a given specificity (SMAGS), for binary classification that finds the linear decision rule, yielding the maximum sensitivity for a given specificity or the maximum specificity for a given sensitivity. We additionally expand the framework …

Analysis Of Systematic Trade-Offs Between Military And Healthcare Expenditure Alongside Gdp Growth Of Select Asian And Western Exporting Economies In The 21st Century, Rahul Balamurugan, Carlos Gershenson, Preethi Nanjundan, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

This study explores the complexity in the trade-offs between military expenditure, healthcare expenditure, and GDP growth across select Asian nations and major weapon-exporting countries, examining how nations allocate finite resources between national security and human well-being over the past two decades. Using a systems science approach, the research integrates Granger causality testing to analyze temporal and directional relationships among GDP growth, military expenditure, and healthcare expenditure, uncovering their dynamic interdependencies. The methodology includes trend and slope analysis, Granger causality testing, outlier detection, and clustering to identify heterogeneity in resource allocation strategies. Developed, weapon-exporting nations exhibit complementary trends, with strong causality …

Children Suspected For Developmental Coordination Disorder In Hong Kong And Associated Health-Related Functioning: A Survey Study, Kathlynne F. Eguia, Sum Kwing Cheung, Kevin K.H. Chung, Catherine M. Capio

Health Sciences Faculty Publications

Children with developmental coordination disorder (DCD) have motor difficulties that interfere with their daily functions. The extent to which DCD affects children in Hong Kong has not been established. In this study, we aimed to estimate the prevalence of children suspected of DCD (sDCD) in Hong Kong and to examine the relationship between motor performance difficulties and health-related functioning. We conducted a cross-sectional survey of parents of children aged 5 to 12 years across Hong Kong (N = 656). The survey consisted of the Developmental Coordination Disorder Questionnaire (DCDQ) and short forms on global health, physical activity, positive affect, and …

The Present And Future Of Ai: Ethical Issues And Research Opportunities, Ankita Srivastava, Marco Marabelli, Danielle Blanch-Hartigan, Jeffrey Moriarty, Evan Carey

Philosophy Faculty Publications

Healthcare is currently a fast-changing industry with AI and generative AI (GenAI) playing a prominent role in the transformation of clinical as well as managerial practices. Clinical practices involve AI to diagnose diseases and develop new drugs and compounds, while managerial practices concern AI-supporting processes such as billing patients and insurance companies, handling electronic medical records, and supporting remote connections with patients, increasingly using virtual and augmented reality. Yet, all these opportunities offered by AI come with challenges involving potential ethical issues, such as discrimination, bias, lack of accessibility, and privacy issues. In March 2024, we organized a panel with …

Evaluation Of Enzyme Activity Predictions For Variants Of Unknown Significance In Arylsulfatase A, Shantanu Jain, Marena Trinidad, Thanh Binh Nguyen, Kaiya Jones, Santiago Diaz Neto, Fang Ge, Ailin Glagovsky, Cameron Jones, Giankaleb Moran, Boqi Wang, Kobra Rahimi, Sümeyra Zeynep Çalıcı, Luis R Cedillo, Silvia Berardelli, Buse Özden, Ken Chen, Panagiotis Katsonis, Amanda Williams, Olivier Lichtarge, Sadhna Rana, Swatantra Pradhan, Rajgopal Srinivasan, Rakshanda Sajeed, Dinesh Joshi, Eshel Faraggi, Robert Jernigan, Andrzej Kloczkowski, Jierui Xu, Zigang Song, Selen Özkan, Natàlia Padilla, Xavier De La Cruz, Rocio Acuna-Hidalgo, Andrea Grafmüller, Laura T Jiménez Barrón, Matteo Manfredi, Castrense Savojardo, Giulia Babbi, Pier Luigi Martelli, Rita Casadio, Yuanfei Sun, Shaowen Zhu, Yang Shen, Fabrizio Pucci, Marianne Rooman, Gabriel Cia, Daniele Raimondi, Pauline Hermans, Sofia Kwee, Ella Chen, Courtney Astore, Akash Kamandula, Vikas Pejaver, Rashika Ramola, Michelle Velyunskiy, Daniel Zeiberg, Reet Mishra, Teague Sterling, Jennifer L Goldstein, Jose Lugo-Martinez, Sufyan Kazi, Sindy Li, Kinsey Long, Steven E Brenner, Constantina Bakolitsa, Predrag Radivojac, Dean Suhr, Teryn Suhr, Wyatt T Clark

Faculty, Staff and Students Publications

Continued advances in variant effect prediction are necessary to demonstrate the ability of machine learning methods to accurately determine the clinical impact of variants of unknown significance (VUS). Towards this goal, the ARSA Critical Assessment of Genome Interpretation (CAGI) challenge was designed to characterize progress by utilizing 219 experimentally assayed missense VUS in the Arylsulfatase A (ARSA) gene to assess the performance of community-submitted predictions of variant functional effects. The challenge involved 15 teams, and evaluated additional predictions from established and recently released models. Notably, a model developed by participants of a genetics and coding bootcamp, trained with standard machine-learning …

Preserving Privacy In Senior Care At Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, Scott Sittig

Shelby Hall Graduate Research Forum Posters

Many seniors prefer to live at home which necessitates research into the application of technologies to provide a safer environment with less caregiver resources. However, the application of home health care (HHC) monitoring for seniors is still in an evolutionary stage. Present HHC systems are produced by private companies with general regulatory guidelines lacking specific care of the elderly. As such, each company that produces such a system claims to have better safety, privacy, and security that their competitors. A pressing issues is devising and applying a general framework for the application of technologies that delivers safety while preserving privacy. …

False Narratives, Real Consequences, Russell W. Cantrell, Matt Campbell

Shelby Hall Graduate Research Forum Posters

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation's role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This …

Analysis Of Nuclear Security And Safety Integration Using Survey Responses And Pairwise Comparison Methods, Sheila V. Gbormittah, Theodore A. Thomas, Jason Timothy Harris

International Journal of Nuclear Security

Integrating nuclear security and safety is important for implementing and sustaining nuclear technology because it promises improved and effective management. This integration is an ongoing effort to ensure that both work together with minimal conflicts. This research aimed to determine the preferred level at which nuclear security and nuclear safety integrate by using the pairwise comparison methods of decision-making. This methodology used survey responses from women nuclear professionals to identify the most-desired criteria at three levels: strategic, operational, and cultural. The strategic level includes actions that government officials and regulators can take. The operational level encompasses actions that deliver the …

Thorium Bioassay Of Miners Revisited, Gregory Hewson, Martin Ralph, Marcus Cattani

Research outputs 2022 to 2026

This study aimed to revisit previous in-vitro thorium studies on workers and reevaluate their significance against the current International Commission on Radiological Protection (ICRP) models for thorium intake. Thorium concentrations in the urine and blood serum of Western Australian mineral sands workers had previously been interpreted using biokinetic models recommended by the ICRP. These findings revealed significant inconsistencies with those of other monitoring methods, including in-vivo lung counting and personal air sampling. Data on thorium concentrations in the urine and blood serum of workers and their exposure records were extracted from the previously published research and assessed using the Taurus …

The Learning Crisis In The United States Three Years After Covid-19, Harry Anthony Patrinos, Maciej Jakubowski, Tomasz Gajderowicz

Education Reform Faculty and Graduate Students Publications

The COVID-19 pandemic caused widespread disruptions to education, with school closures affecting over one billion children. These closures, aimed at reducing virus transmission, resulted in significant learning losses, particularly in mathematics and science. Using United States data from TIMSS, this study analyzes the impact of school closure on learning outcomes. The losses amount to 0.36 SD for mathematics and 0.16 SD for science. The declines are similar across grades. The average decline in mathematics performance among U.S. students is substantially greater than the global average. n science, the decline observed among U.S. students does not significantly differ from the global …

Modifiable And Non-Modifiable Risk Factors For Dementia Among Non-Hispanic White And Black Populations Aged 50-64 In The United States, 2006-2016, Jingkai Wei, Matthew C. Lohman Ph.D., Monique J. Brown, James W. Hardin, Chih-Hsiang Yang, Anwar T. Nerchant, Daniela B. Friedman

Faculty Publications

Background and Objectives

Research Design and Methods

Adverse Childhood Experiences, Resilience, And Syringe Services Program Attendance Among Persons Who Inject Drugs In Northeast Georgia, Usa: A Mediation Analysis, Mohammad Rifat Haider, Samantha Clinton, Monique J. Brown, Nathan B. Hansen

Faculty Publications

Background: Syringe services programs (SSP) are evidence-based venues offering harm reduction services to persons who inject drugs (PWID), such as sterile syringes, STI/HIV testing, and linkage to care to decrease drug use-related morbidities and mortalities. Adverse childhood experiences (ACEs) have been linked with reduced resilience, while increased resilience can help PWID attend SSPs. This study examined the potential mediating role of resilience between ACEs and SSP attendance among PWID.

Methods: Data were collected from adult HIV-negative PWID in northeast Georgia, between February-December 2023 (N = 173). Data were collected on SSP attendance (Yes vs. No), resilience, and ACEs. Covariates included …

Geographic Disparities In Unpaid Caregiving, Emma Kathryn Boswell, Monique J. Brown Ph.D., Mph, Lorie Donelle Phd, Rn, Fcan, Nicholas Yell, Taryn Farrell, Peiyin Hung Ph.D., Elizabeth Crouch Ph.D.

Faculty Publications

Purpose: An updated, nationally representative examination of rural–urban differences in the experiences, health, and well-being of caregivers is needed; previous research on this topic uses older data or has limited generalizability. This study examines rural–urban differences in the characteristics, experiences, and health of caregivers. Methods: The 2021–2022 Behavioral Risk Factor Surveillance System (n = 44,274 unpaid caregivers) was used, with rurality defined according to the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme. Chi-square tests compared rural–urban differences in these caregivers’ characteristics, including demographic factors, caregiving intensity (e.g., weekly hours spent caregiving, reason for caregiving, past-month ADL/IADL assistance), …

Going Green In Dermatology, Rahib K. Islam, Victoria T. Tong, Shari R. Lipner

School of Medicine Faculty Publications

No abstract provided.

Assessment Of Skin Fibrosis In A Murine Model Of Systemic Sclerosis With Multifunctional Optical Coherence Tomography, Harshdeep Singh Chawla, Yanping Chen, Minghua Wu, Pavel Nikitin, Jessica Gutierrez, Chandra Mohan, Manmohan Singh, Salavat R Aglyamov, Shervin Assassi, Kirill V Larin

Faculty, Staff and Student Publications

Significance: Systemic sclerosis (SSc) is a chronic idiopathic disease that causes immune dysregulation, vasculopathy, and organ fibrosis that affects more than 3 million people in the US alone. The modified Rodnan skin score (mRSS) is the current gold standard for diagnosing and staging skin fibrosis in SSc. However, mRSS is subjective, requires extensive training, and has high observer variability.

Aim: We aim to provide a quantitative method for the assessment of fibrosis.

Approach: We utilized optical coherence tomography (OCT), its extensions, optical coherence elastography (OCE), and OCT angiography (OCTA) to evaluate SSc-like fibrosis and therapy response in a mouse model. …

Bpen: Brain Posterior Evidential Network For Trustworthy Brain Imaging Analysis, Kai Ye, Haoteng Tang, Siyuan Dai, Igor Fortel, Paul M. Thompson, R. Scott Mackin, Alex Leow, Heng Huang, Liang Zhan

Computer Science Faculty Publications

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological conditions. Despite these achievements, the aspect of prediction uncertainty has been relatively underexplored in brain fMRI data analysis. Accurate uncertainty estimation is essential for trustworthy learning, given the challenges associated with brain fMRI data acquisition and the potential diagnostic implications for patients. To address this gap, we introduce a novel posterior evidential network, named the Brain Posterior Evidential Network (BPEN), designed to capture both aleatoric and epistemic uncertainty in …

Proceedings Of The National Cancer Institute Workshop On Combining Immunotherapy With Radiotherapy: Challenges And Opportunities For Clinical Translation, Zachary S Morris, Sandra Demaria, Arta M Monjazeb, Silvia C Formenti, Ralph R Weichselbaum, James Welsh, Heiko Enderling, Jonathan D Schoenfeld, Joshua D Brody, Heather M Mcgee, Michele Mondini, Michael S Kent, Kristina H Young, Lorenzo Galluzzi, Sana D Karam, Willemijn S M E Theelen, Joe Y Chang, Mai Anh Huynh, Adi Daib, Sean Pitroda, Caroline Chung, Raphael Serre, Clemens Grassberger, Jie Deng, Quaovi H Sodji, Anthony T Nguyen, Ravi B Patel, Simone Krebs, Anusha Kalbasi, Caroline Kerr, Claire Vanpouille-Box, Logan Vick, Todd A Aguilera, Irene M Ong, Fernanda Herrera, Hari Menon, Deedee Smart, Jalal Ahmed, Robyn D Gartrell, Christina L Roland, Fatemeh Fekrmandi, Binita Chakraborty, Eric H Bent, Tracy J Berg, Alan Hutson, Samir Khleif, Andrew G Sikora, Lawrence Fong

Faculty, Staff and Student Publications

Radiotherapy both promotes and antagonises tumour immune recognition. Some clinical studies show improved patient outcomes when immunotherapies are integrated with radiotherapy. Safe, greater than additive, clinical response to the combination is limited to a subset of patients, however, and how radiotherapy can best be combined with immunotherapies remains unclear. The National Cancer Institute-Immuno-Oncology Translational Network-Society for Immunotherapy of Cancer-American Association of Immunology Workshop on Combining Immunotherapy with Radiotherapy was convened to identify and prioritise opportunities and challenges for radiotherapy and immunotherapy combinations. Sessions examined the immune effects of radiation, barriers to anti-tumour immune response, previous clinical trial data, immunological and …

Qsp Modeling Shows Pathological Synergism Between Insulin Resistance And Amyloid-Beta Exposure In Upregulating Vcam1 Expression At The Bbb Endothelium, Zengtao Wang, Vaishnavi Veerareddy, Xiaojiao Tang, Kevin J Thompson, Sunil Krishnan, Krishna R Kalari, Karunya K Kandimalla

Faculty, Staff and Student Publications

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance, is closely associated with Alzheimer's disease (AD). Cerebrovascular dysfunction is manifested in both T2DM and AD, and is often considered as a pathological link between the two diseases. Insulin signaling regulates critical functions of the blood-brain barrier (BBB), and endothelial insulin resistance could lead to BBB dysfunction, aggravating AD pathology. However, insulin signaling is intrinsically dynamic and involves interactions among numerous molecular mediators. Hence, a mechanistic systems biology model is needed to understand how insulin regulates BBB physiology and the consequences of its impairment in T2DM and AD. In this study, …

Robust Automated Method Of Spatial Resolution Measurement In Radiotherapy Ct Simulation Images, Pavel Govyadinov, Rick R Layman, Tucker Netherton, Raymond Mumme, Aaron K Jones, Laurence E Court, Moiz Ahmad

Faculty, Staff and Student Publications

Background: Variation in imaging protocol, patient positioning, and the presence of artifacts can vary image quality in CT images used for radiotherapy planning. Automated methods for spatial resolution (SR) estimation exist but require further investigation and validation for wider adoption.

Purpose: To validated previously existing algorithm for SR estimation and introduce improvements that make it robust to patient positioning, CT protocol, site, and artifacts.

Method: A reference algorithm based on the previous gold standard was recreated and modified to improve robustness. The algorithms were tested on three different datasets: (1) a cylindrical ACR CT QC phantom scanned using a Siemens …

Difference-Makers For Collecting Sexual Orientation And Gender Identity Data In Oncology Settings, Mandi L Pratt-Chapman, Edward J Miech, Megan A Mullins, Shine Chang, Gwendolyn P Quinn, Shail Maingi, Matthew B Schabath, Charles Kamen

Faculty, Staff and Student Publications

Purpose: The purpose of this analysis was to identify key difference-making conditions that distinguish oncology institutions that collect sexual orientation and gender identity (SOGI) data across a sample of American Society of Clinical Oncology (ASCO) members.

Methods: From October to November 2020, an anonymous 54-item web-based survey was distributed to ASCO members. Coincidence analysis was used to identify difference-making conditions for the collection of SOGI data.

Results: ASCO members' responses to just three items consistently distinguished practices that reported collecting both SO and GI data (n = 25) from those who did not (n = 20): (1)."Do you ask your …

A Sample Size Analysis Of A Mathematical Model Of Longitudinal Tumor Volume And Progression-Free Survival For Bayesian Individual Dynamic Predictions In Recurrent High-Grade Glioma, Daniel J Glazar, Solmaz Sahebjam, Hsiang-Husan M Yu, Dung-Tsa Chen, Menal Bhandari, Heiko Enderling

Faculty, Staff and Student Publications

Patients with recurrent high-grade glioma (rHGG) have a poor prognosis with median progression-free survival (PFS) ofheterogenous, suggesting a clinical need for prognostic models. Bayesian data analysis can exploit individual patient follow-up imaging studies to adaptively predict the risk of progression. We propose a novel sample size analysis for Bayesian individual dynamic predictions and demonstrate proof of principle. We coupled a nonlinear mixed effects tumor growth inhibition model with a survival model. Longitudinal tumor volumes and time-to-progression were simulated for 2000 in silico rHGG patients. Bayesian individual dynamic predictions of PFS curves were evaluated using area under the receiver operating characteristic …

Rapid Development Of An Online Tracker To Communicate The Human Impact Of Abruptly Halting Pepfar Support, Brooke E Nichols, Elvin H Geng, Eric Moakley, Andrew N Phillips, Jeffrey W Imai-Eaton, John Stover, Edinah Mudimu, Anna Grimsrud

2020-Current year OA Pubs

No abstract provided.

Leveraging Artificial Intelligence And Machine Learning To Accelerate Discovery Of Disease-Modifying Therapies In Type 1 Diabetes., Melanie R. Shapiro, Erin M. Tallon, Matthew E. Brown, Amanda L. Posgai, Mark A. Clements, Todd M. Brusko

Manuscripts, Articles, Book Chapters and Other Papers

Progress in developing therapies for the maintenance of endogenous insulin secretion in, or the prevention of, type 1 diabetes has been hindered by limited animal models, the length and cost of clinical trials, difficulties in identifying individuals who will progress faster to a clinical diagnosis of type 1 diabetes, and heterogeneous clinical responses in intervention trials. Classic placebo-controlled intervention trials often include monotherapies, broad participant populations and extended follow-up periods focused on clinical endpoints. While this approach remains the 'gold standard' of clinical research, efforts are underway to implement new approaches harnessing the power of artificial intelligence and machine learning …

Artificial Intelligence In Surgical Coding: Evaluating Large Language Models For Current Procedural Terminology Accuracy In Hand Surgery, Emily Isch, Jamie Lee, D. Mitchell Self, Abhijeet Sambangi, Theodore E. Habarth-Morales, John R. Vaile, E. J. Caterson

Department of Surgery Faculty Papers

PURPOSE: The advent of large language models (LLMs) like ChatGPT has introduced notable advancements in various surgical disciplines. These developments have led to an increased interest in the use of LLMs for Current Procedural Terminology (CPT) coding in surgery. With CPT coding being a complex and time-consuming process, often exacerbated by the scarcity of professional coders, there is a pressing need for innovative solutions to enhance coding efficiency and accuracy.

METHODS: This observational study evaluated the effectiveness of five publicly available large language models-Perplexity.AI, Bard, BingAI, ChatGPT 3.5, and ChatGPT 4.0-in accurately identifying CPT codes for hand surgery procedures. A …

Multiethnic Growth Standards For Fetal Body Composition And Organ Volumes Derived From 3d Ultrasonography, Katherine L Grantz, Wesley Lee, Lauren M Mack, Magdalena Sanz Cortes, Luis F Goncalves, Jimmy Espinoza, Roger B Newman, William A Grobman, Ronald J Wapner, Karin Fuchs, Mary E D'Alton, Daniel W Skupski, John Owen, Anthony Sciscione, Deborah A Wing, Michael P Nageotte, Angela C Ranzini, Edward K Chien, Sabrina Craigo, Seth Sherman, Robert E Gore-Langton, Dian He, Fasil Tekola-Ayele, Cuilin Zhang, Jagteshwar Grewal, Zhen Chen

Faculty, Staff and Student Publications

Background: A major goal of contemporary obstetrical practice is to optimize fetal growth and development throughout pregnancy. To date, fetal growth during prenatal care is assessed by performing ultrasonographic measurement of 2-dimensional fetal biometry to calculate an estimated fetal weight. Our group previously established 2-dimensional fetal growth standards using sonographic data from a large cohort with multiple sonograms. A separate objective of that investigation involved the collection of fetal volumes from the same cohort.

Objective: The Fetal 3D Study was designed to establish standards for fetal soft tissue and organ volume measurements by 3-dimensional ultrasonography and compare growth trajectories with …

Patient Consent And The Right To Notice And Explanation Of Ai Systems Used In Health Care, Meghan E Hurley, Benjamin H Lang, Kristin Marie Kostick-Quenet, Jared N Smith, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

Given the need for enforceable guardrails for artificial intelligence (AI) that protect the public and allow for innovation, the U.S. Government recently issued a Blueprint for an AI Bill of Rights which outlines five principles of safe AI design, use, and implementation. One in particular, the right to notice and explanation, requires accurately informing the public about the use of AI that impacts them in ways that are easy to understand. Yet, in the healthcare setting, it is unclear what goal the right to notice and explanation serves, and the moral importance of patient-level disclosure. We propose three normative functions …

Evaluating Dry Air Personnel Decontamination Of Methyl Salicylate As A Chemical Agent Surrogate In Extreme Cold Environments To Reduce Airborne Risks Using A Manikin, Lance E. Campbell

Theses and Dissertations

This research investigated a mobile air shower as an alternative to water washing for personnel chemical decontamination in Arctic environments, where traditional methods like disrobing and rinsing are impractical. Interest in Arctic operations has grown with recent U.S. military focus on strategic advancements by Russia and China, yet research on air shower effectiveness for chemical decontamination remains limited. This study examined whether a commercial off-the-shelf air shower could effectively decontaminate methyl salicylate (MES), a surrogate for chemical warfare blister agents, from a manikin outfitted in military cold-weather gear. Researchers used a ppbRAE 3000 photo-ionization detector to measure MES concentrations following …

Air-Based Chemical Patient Decontamination Methodologies For Arctic Regions Using Methly Salicylate As A Chemical Agent Surrogate On A Litter-Bound Manikin, Marcus D. Shadd

Theses and Dissertations

This study evaluated a mobile air shower for patient decontamination without disrobing or rinsing, an alternative for Arctic conditions where water is scarce. A manikin in extreme cold weather gear was exposed to 10 µL of methyl salicylate (MeS), a sulfur mustard surrogate, and placed in a horizontal chamber on a military litter. Airborne MeS was measured using a ppbRAE 3000 detector to assess inhalation risk for the patient and decontamination team. Three methods were tested: an air-knife system, paper towels, and no decontamination, with 10 trials each (30 total). ANOVA analysis showed significant reductions in airborne MeS with air-knife …

Harmonizing Innovation: The Beatles, Emi, And The Birth Of Computed Tomography Imaging, Matthew A. Daniel, Alexander Holland, Saptarshi Biswas

HCA Healthcare Journal of Medicine

Computed tomography (CT) imaging has become a cornerstone of modern medical diagnostics, thanks to the groundbreaking work of Sir Godfrey Hounsfield. However, the significant role played by his employer, Electric and Musical Industries (EMI), in providing financial support for his research is often overlooked. In this paper, we explore the connection between EMI's success in the music industry, particularly its signing of the Beatles, and Hounsfield's pioneering work on CT imaging. EMI’s success in the music industry provided the financial stability for Hounsfield's research endeavors. In 1971, he developed the first CT scanner, which revolutionized diagnostic medicine. His collaboration with …

Reducing Medical Waste, George M. Jeha, Stanislav N. Tolkachjov

School of Medicine Faculty Publications

No abstract provided.