Medicine and Health Sciences Commons^™

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Ling, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation …

Ambient Air Pollution Exposure And Increasing Depressive Symptoms In Older Women: The Mediating Role Of The Prefrontal Cortex And Insula, Andrew J. Petkus, Susan M. Resnick, Xinhui Wang, Daniel P. Beavers, Mark A. Espeland, Margaret Gatz, Tara Gruenewald, Joshua Millstein, Helena C. Chui, Joel D. Kaufman, Joann E. Manson, Gregory A. Wellenius, Eric A. Whitsel, Keith Widaman, Diana Younan, Jiu-Chiuan Chen

Psychology Faculty Articles and Research

Exposures to fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) have been associated with the emergence of depressive symptoms in older adulthood, although most studies used cross-sectional outcome measures. Elucidating the brain structures mediating the adverse effects can strengthen the causal role between air pollution and increasing depressive symptoms. We evaluated whether smaller volumes of brain structures implicated in late-life depression mediate associations between ambient air pollution exposure and changes in depressive symptoms. This prospective study included 764 community-dwelling older women (aged 81.6 ± 3.6 in 2008–2010) from the Women's Health Initiative Memory Study (WHIMS) Magnetic …

Comparison Of Human Urinary Exosomes Isolated Via Ultracentrifugation Alone Versus Ultracentrifugation Followed By Sec Column-Purification, Kun Huang, Sudha Garimella, Alyssa Clay-Gilmour, Lucia Vojtech, Bridget Armstrong, Madison Bessonny, Alexis Stamatikos

Faculty Publications

Chronic kidney disease is a progressive, incurable condition that involves a gradual loss of kidney function. While there are no non-invasive biomarkers available to determine whether individuals are susceptible to developing chronic kidney disease, small RNAs within urinary exosomes have recently emerged as a potential candidate to use for assessing renal function. Ultracentrifugation is the gold standard for urinary exosome isolation. However, extravesicular small RNA contamination can occur when isolating exosomes from biological fluids using ultracentrifugation, which may lead to misidentifying the presence of certain small RNA species in human urinary exosomes. Therefore, we characterized human urinary exosomal preparations isolated …

An Efficient Method Of Evaluating Multiple Concurrent Management Actions On Invasive Populations, Amy J. Davis, Randy Farrar, Brad Jump, Parker Hall, Travis Guerrant, Kim M. Pepin

United States Department of Agriculture Wildlife Services: Staff Publications

Evaluating the efficacy of management actions to control invasive species is crucial for maintaining funding and to provide feedback for the continual improvement of management efforts. However, it is often difficult to assess the efficacy of control methods due to limited resources for monitoring. Managers may view effort on monitoring as effort taken away from performing management actions. We developed a method to estimate invasive species abundance, evaluate management effectiveness, and evaluate population growth over time from a combination of removal activities (e.g., trapping, ground shooting) using only data collected during removal efforts (method of removal, date, location, number of …

A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang

Faculty Publications

Immunotherapy is an innovative treatment that enlists the patient's immune system to battle tumors. The optimal dose for treating patients with an immunotherapeutic agent may differ according to their biomarker status. In this article, we propose a biomarker-based phase I/II dose-finding design for identifying subgroup-specific optimal dose for immunotherapy (BSOI) that jointly models the immune response, toxicity, and efficacy outcomes. We propose parsimonious yet flexible models to borrow information across different types of outcomes and subgroups. We quantify the desirability of the dose using a utility function and adopt a two-stage dose-finding algorithm to find the optimal dose for each …

Usability Of Health-Related Websites By Filipino-American Adults And Nursing Informatics Experts, Kathleen Begonia

Dissertations, Theses, and Capstone Projects

Filipino-Americans are an understudied minority group with high prevalence and mortality from chronic conditions, such as cardiovascular disease and diabetes. Facing barriers to care and lack of culturally appropriate health resources, they frequently use the internet to obtain health information. It is unknown whether they perceive health-related websites to be useful or easy to use because there are no published usability studies involving this population. Using the Technology Acceptance Model as a theoretical framework, this study investigated the difference between website design ratings by experts and the perceptions of Filipino-American users to determine if usability guidelines influenced the perceived ease …

In A Digitally Connected World Through Likes, Hashtags And Followers - Advancing Surgical Research Through A Social Media: A Narrative Review, Sabah Uddin Saqib, Qamar` Riaz, Russell Seth Martins, Amna Riaz, Hasnain Zafar

Department for Educational Development

In this era of modern information technology, the world is now digitally connected through various platforms on social media, which has changed the way medical professionals work, communicate and learn. The use of social media in surgery is expanding, and it is now becoming an essential tool for surgical training, research and networking. Articles, journal clubs and surgical conferences are within reach of everyone regardless of geographical location worldwide. Electronic publications have now resoundingly replaced printed editions of journals. Collaborative research through social media platforms helps collect diverse data, enhancing the research's global generalisability. The current narrative review was planned …

Verticox: Vertically Distributed Cox Proportional Hazards Model Using The Alternating Direction Method Of Multipliers, Wenrui Dai, Xiaoqian Jiang, Luca Bonomi, Yong Li, Hongkai Xiong, Lucila Ohno-Machado

Faculty, Staff and Student Publications

The Cox proportional hazards model is a popular semi-parametric model for survival analysis. In this paper, we aim at developing a federated algorithm for the Cox proportional hazards model over vertically partitioned data (i.e., data from the same patient are stored at different institutions). We propose a novel algorithm, namely VERTICOX, to obtain the global model parameters in a distributed fashion based on the Alternating Direction Method of Multipliers (ADMM) framework. The proposed model computes intermediary statistics and exchanges them to calculate the global model without collecting individual patient-level data. We demonstrate that our algorithm achieves equivalent accuracy for the …

Diagnosis Of Polypoidal Choroidal Vasculopathy From Fluorescein Angiography Using Deep Learning, Yu-Yeh Tsai, Wei-Yang Lin, Shih-Jen Chen, Paisan Ruamviboonsuk, Cheng-Ho King, Chia-Ling Tsai

Publications and Research

Purpose: To differentiate polypoidal choroidal vasculopathy (PCV) from choroidal neovascularization (CNV) and to determine the extent of PCV from fluorescein angiography (FA) using attention-based deep learning networks.

Methods: We build two deep learning networks for diagnosis of PCV using FA, one for detection and one for segmentation. Attention-gated convolutional neural network (AG-CNN) differentiates PCV from other types of wet age-related macular degeneration. Gradient-weighted class activation map (Grad-CAM) is generated to highlight important regions in the image for making the prediction, which offers explainability of the network. Attention-gated recurrent neural network (AG-PCVNet) for spatiotemporal prediction is applied for segmentation of PCV. …

Economics Of Cormorant Predation On Catfish Farms, Carole Engle, Ganesh Kumar, Terrel Christie, Brian S. Dorr, Brian Davis, Luke Roy, Anita Kelly

United States Department of Agriculture Wildlife Services: Staff Publications

The Double-crested Cormorant is the primary avian predator on catfish farms causing significant economic losses primarily due to 1) on-farm expenditures related to bird-management activities and 2) value of the catfish lost to cormorants. This comprehensive economic study quantified these two economic effects by surveying catfish farms in the delta regions of Mississippi and Arkansas. On-farm expenditures for bird scaring were used to quantify bird-management costs. Economic losses from fish consumed by cormorants were quantified by evaluating data from field studies of the abundance, distribution, and diet of cormorants in the Mississippi delta. This study found that catfish farmers …

A Deep Dive Into The Impact Of Covid-19 On Software Development, Paulo Anselmo Da Mota Silveira Neto, Umme Ayda Mannan, Eduardo Santana De Almeida, Nachiappan Nagappan, David Lo, Pavneet Singh Kochhar, Cuiyun Gao, Iftekhar Ahmed

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic is considered as the most crucial global health calamity of the century. It has impacted different business sectors around the world and software development is not an exception. This study investigates the impact of COVID-19 on software projects and software development professionals. We conducted a mining software repository study based on 100 GitHub projects developed in Java using ten different metrics. Next, we surveyed 279 software development professionals for better understanding the impact of COVID-19 on daily activities and wellbeing. We identified 12 observations related to productivity, code quality, and wellbeing. Our findings highlight that the impact …

Field Study In Deploying Restless Multi-Armed Bandits: Assisting Non-Profits In Improving Maternal And Child Health, Aditya Mate, Lovish Madan, Aparna Taneja, Neha Madhiwalla, Shresth Verma, Gargi Singh, Aparna Hegde, Pradeep Varakantham, Milind Tambe

Research Collection School Of Computing and Information Systems

The widespread availability of cell phones has enabled non-profits to deliver critical health information to their beneficiaries in a timely manner. This paper describes our work to assist non-profits that employ automated messaging programs to deliver timely preventive care information to beneficiaries (new and expecting mothers) during pregnancy and after delivery. Unfortunately, a key challenge in such information delivery programs is that a significant fraction of beneficiaries drop out of the program. Yet, non-profits often have limited health-worker resources (time) to place crucial service calls for live interaction with beneficiaries to prevent such engagement drops. To assist non-profits in optimizing …

Characteristics And Assessing Biological Risks Of Airborne Bacteria In Waste Sorting Plant, Abbas Norouzian Baghani, Somayeh Golbaz, Gholamreza Ebrahimzadeh, Marcelo I. Guzman, Mahdieh Delikhoon, Mehdi Jamshidi Rastani, Abdullah Barkhordari, Ramin Nabizadeh

Chemistry Faculty Publications

Examining the concentration and types of airborne bacteria in waste paper and cardboard sorting plants (WPCSP) is an urgent matter to inform policy makers about the health impacts on exposed workers. Herein, we collected 20 samples at 9 points of a WPCSP every 6 winter days, and found that the most abundant airborne bacteria were positively and negatively correlated to relative humidity and temperature, respectively. The most abundant airborne bacteria (in units of CFU m⁻³) were: Staphylococcus sp. (72.4) > Micrococcus sp. (52.2) > Bacillus sp. (30.3) > Enterococcus sp. (24.0) > Serratia marcescens (20.1) > E. coli (19.1) > Pseudomonas sp. (16.0) > Nocardia …

Understanding Deep Learning - Challenges And Prospects, Niha Adnan, Fahad Umer

Department of Surgery Docs

The developments in Artificial Intelligence have been on the rise since its advent. The advancements in this field have been the innovative research area across a wide range of industries, making its incorporation in dentistry inevitable. Artificial Intelligence techniques are making serious progress in the diagnostic and treatment planning aspects of dental clinical practice. This will ultimately help in the elimination of subjectivity and human error that are often part of radiographic interpretations, and will improve the overall efficiency of the process. The various types of Artificial Intelligence algorithms that exist today make the understanding of their application quite complex. …

Perioperative Registries In Resource-Limited Settings: The Way Forward For Pakistan, Usama Waqar, Shaheer Ahmed, Ayesha Nasir Hameed, Namrah Aziz, Hina Inam

Medical College Documents

Capable of improving surgical quality, perioperative registries can allow performance benchmarking, reliable reporting and the development of risk-prediction models. Well established in high-income countries, perioperative registries remain limited in lower- and middle-income countries due to several challenges. First, ensuring comprehensive data entry forums to power the registries is difficult because of limited electronic medical records requiring sustained efforts to develop and integrate these into practice. Second, lack of adequate expertise and resources to develop and maintain registry software necessitates the involvement of software developers and information technology personnel. Third, case ascertainment and item completion are challenging secondary to poor-quality medical …

Mathematics For The Masses: Door-To-Door Missionaries Of Math And Twelve-Step Recovery Programs, Daniel S. Helman

Journal of Humanistic Mathematics

Conversion of strangers, or proselytizing, is a feature of a range of groups for religious, organizational and other aims. In twelve-step recovery programs, such as Alcoholics Anonymous, belief in a higher power is a requirement for working the steps to recovery. People are encouraged to find a higher power of their own understanding. This paper presents a model for using mathematics as a higher power, and shows how recovery works with mathematics in that role instead of a more traditional higher power such as God. A contemplative definition of math is given along with a description of a three-categoried epistemology: …

Perspectives Of Orthodontists Of The Diagnosis, Prevention, And Management Of White Spot Lesions: A Qualitative Study, Salwa Taibah, Neamat Hassan Abubakr Hassan, Hassan Ziada

Dental Medicine Faculty Research

Aims: Several factors influence the development of white spot lesions (WSLs), and one of these is fixed orthodontic appliances. This study aims to evaluate the awareness, preventive strategies, and management of WSLs among a group of Orthodontists. Materials and Methods: A qualitative methodology was applied; four focus groups made up a purposive sample from Orthodontists with various training backgrounds while working within the same healthcare services. Results: Three main themes emerged: awareness and ability to diagnose WSLs, perceived influences on the development of WSLs, and prevention and management strategies and barriers to care delivery. All focus groups agreed that there …

Blood Flow Restriction Training After Patellar Instability (Brains Trial), Benjamin D. Brightwell, Austin V. Stone, Xiaojuan Li, Peter A. Hardy, Katherine L. Thompson, Brian W. Noehren, Cale A. Jacobs

Orthopaedic Surgery and Sports Medicine Faculty Publications

Background

Patellar instability is a common and understudied condition that disproportionally affects athletes and military personnel. The rate of post-traumatic osteoarthritis that develops following a patellar dislocation can be up to 50% of individuals 5–15 years after injury. Conservative treatment is the standard of care for patellar instability however, there are no evidence-informed rehabilitation guidelines in the scientific literature. The purpose of this study is to assess the effectiveness of blood-flow restriction training (BFRT) for patellar instability. Our hypotheses are that this strategy will improve patient-reported outcomes and accelerate restoration of symmetric strength and knee biomechanics necessary to safely return …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub

Computer Vision Faculty Publications

Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class …

Research Priorities Of Applying Low-Cost Pm2.5 Sensors In Southeast Asian Countries, Shih-Chun Candice Lung, To Thi Hien, Maria Obiminda L. Cambaliza, Ohnmar May Tin Hlaing, Nguyen Thi Kim Oanh, Mohd Talib Latif, Puji Lestari, Abdus Salam, Shih-Yu Lee, Wen-Cheng Vincent Wang

Physics Faculty Publications

The low-cost and easy-to-use nature of rapidly developed PM2.5 sensors provide an opportunity to bring breakthroughs in PM2.5 research to resource-limited countries in Southeast Asia (SEA). This review provides an evaluation of the currently available literature and identifies research priorities in applying low-cost sensors (LCS) in PM2.5 environmental and health research in SEA. The research priority is an outcome of a series of participatory workshops under the umbrella of the International Global Atmospheric Chemistry Project–Monsoon Asia and Oceania Networking Group (IGAC–MANGO). A literature review and research prioritization are conducted with a transdisciplinary perspective of providing useful scientific evidence in assisting …

Machine Learning For Predicting Risk Of Early Dropout In A Recovery Program For Opioid Use Disorder, Assaf Gottlieb, Andrea Yatsco, Christine Bakos-Block, James R Langabeer, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

BACKGROUND: An increase in opioid use has led to an opioid crisis during the last decade, leading to declarations of a public health emergency. In response to this call, the Houston Emergency Opioid Engagement System (HEROES) was established and created an emergency access pathway into long-term recovery for individuals with an opioid use disorder. A major contributor to the success of the program is retention of the enrolled individuals in the program.

METHODS: We have identified an increase in dropout from the program after 90 and 120 days. Based on more than 700 program participants, we developed a machine learning …

Pparα And Pparγ Activation Is Associated With Pleural Mesothelioma Invasion But Therapeutic Inhibition Is Ineffective, M. Lizeth Orozco Morales, Catherine A. Rinaldi, Emma De Jong, Sally M. Lansley, Joel P. A. Gummer, Bence Olasz, Shabarinath Nambiar, Danika E. Hope, Thomas H. Casey, Y. C. Gary Lee, Connull Leslie, Gareth Nealon, David M. Shackleford, Andrew K. Powell, Marina Grimaldi, Patrick Balaguer, Rachael M. Zemek, Anthony Bosco, Matthew J. Piggott, Alice Vrielink, Richard A. Lake, W. Joost Lesterhuis

Research outputs 2022 to 2026

Mesothelioma is a cancer that typically originates in the pleura of the lungs. It rapidly invades the surrounding tissues, causing pain and shortness of breath. We compared cell lines injected either subcutaneously or intrapleurally and found that only the latter resulted in invasive and rapid growth. Pleural tumors displayed a transcriptional signature consistent with increased activity of nuclear receptors PPARα and PPARγ and with an increased abundance of endogenous PPAR-activating ligands. We found that chemical probe GW6471 is a potent, dual PPARα/γ antagonist with anti-invasive and anti-proliferative activity in vitro. However, administration of GW6471 at doses that provided sustained plasma …

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …

Scanner: A Web Platform For Annotation, Visualization And Sharing Of Single Cell Rna-Seq Data, Guoshuai Cai, Xuanxuan Yu, Choonhan Youn, Jun Zhou, Feifei Xiao

Faculty Publications

In recent years, efficient scRNA-seq methods have been developed, enabling the transcriptome profiling of single cells massively in parallel. Meanwhile, its high dimensionality and complexity bring challenges to the data analysis and require extensive collaborations between biologists and bioinformaticians and/or biostatisticians. The communication between these two units demands a platform for easy data sharing and exploration. Here we developed Single-Cell Transcriptomics Annotated Viewer (SCANNER), as a public web resource for the scientific community, for sharing and analyzing scRNA-seq data in a collaborative manner. It is easy-to-use without requiring special software or extensive coding skills. Moreover, it equipped a real-time database …

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub

Computer Vision Faculty Publications

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep …

Sociodemographic And Clinical Characteristics Associated With Improvements In Quality Of Life For Participants With Opioid Use Disorder, Assaf Gottlieb, Christine Bakos-Block, James R Langabeer, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

Background: The Houston Emergency Opioid Engagement System was established to create an access pathway into long-term recovery for individuals with opioid use disorder. The program determines effectiveness across multiple dimensions, one of which is by measuring the participant's reported quality of life (QoL) at the beginning of the program and at successive intervals.

Methods: A visual analog scale was used to measure the change in QoL among participants after joining the program. We then identified sociodemographic and clinical characteristics associated with changes in QoL.

Results: 71% of the participants (n = 494) experienced an increase in their QoL scores, …

Case Study: Degenerative Joint Disease In Canines, Zachary B. Lawrence, Rusty Rogers, Emily Schmitt Lavin

Mako: NSU Undergraduate Student Journal

Degenerative joint disease (DJD) is the gradual degeneration of cartilage in joints, resulting in pain for the affected areas. This study focused on Lacy (name changed for privacy), a 10-year-old spayed female chihuahua mix, that was clinically diagnosed for DJD and treated by Dr. Rogers over a period of 15 months. DJD is typically treated through a combination of pharmacological management, nonpharmacological treatment, and changes in lifestyle. Pharmacological treatment utilized pain medications, such as Gabapentin and Tramadol. Nonpharmacological treatment and changes in lifestyle involve methods, such as maintaining an ideal body weight, to decrease pain and increase mobility. However, during …

A Keyword-Enhanced Approach To Handle Class Imbalance In Clinical Text Classification, Andrew E. Blanchard, Shang Gao, Hong Jun Yoon, J. Blair Christian, Eric B. Durbin, Xiao Cheng Wu, Antoinette Stroup, Jennifer Doherty, Stephen M. Schwartz, Charles Wiggins, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi

School of Public Health Faculty Publications

Recent applications ofdeep learning have shown promising results for classifying unstructured text in the healthcare domain. However, the reliability of models in production settings has been hindered by imbalanced data sets in which a small subset of the classes dominate. In the absence of adequate training data, rare classes necessitate additional model constraints for robust performance. Here, we present a strategy for incorporating short sequences of text (i.e. keywords) into training to boost model accuracy on rare classes. In our approach, we assemble a set of keywords, including short phrases, associated with each class. The keywords are then used as …

Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model, Nicole Allison S. Co, Jason Limcaco, Hans Calvin L. Tan, Ma. Regina Justina E. Estuar, Christian E. Pulmano, Dennis Andrew Villamor, Quirino Sugon Jr, Maria Cristina G. Bautista, Paulyn Jean Acacio-Claro

Graduate School of Business Publications

The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses …