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Artificial Intelligence In Cardiovascular Medicine: Historical Overview, Current Status, And Future Directions, Zvonimir Krajcer

The Texas Heart Institute Journal

Artificial intelligence and machine learning are rapidly gaining popularity in every aspect of our daily lives, and cardiovascular medicine is no exception. Here, we provide physicians with an overview of the past, present, and future of artificial intelligence applications in cardiovascular medicine. We describe essential and powerful examples of machine-learning applications in industry and elsewhere. Finally, we discuss the latest technologic advances, as well as the benefits and limitations of artificial intelligence and machine learning in cardiovascular medicine.

International Stroke Genetics Consortium Recommendations For Studies Of Genetics Of Stroke Outcome And Recovery, Arne G Lindgren, Jin-Moo Lee, Et Al

2020-Current year OA Pubs

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable …

Clinical Opinion: The Diagnosis And Management Of Suspected Fetal Growth Restriction: An Evidence-Based Approach, Christoph C Lees, Roberto Romero, Tamara Stampalija, Andrea Dall'asta, Greggory A Devore, Federico Prefumo, Tiziana Frusca, Gerard H A Visser, John C Hobbins, Ahmet A Baschat, Caterina M Bilardo, Henry L Galan, Stuart Campbell, Dev Maulik, Francesc Figueras, Wesley Lee, Julia Unterscheider, Herbert Valensise, Fabricio Da Silva Costa, Laurent J Salomon, Liona C Poon, Enrico Ferrazzi, Giancarlo Mari, Giuseppe Rizzo, John C Kingdom, Torvid Kiserud, Kurt Hecher

Faculty, Staff and Students Publications

This study reviewed the literature about the diagnosis, antepartum surveillance, and time of delivery of fetuses suspected to be small for gestational age or growth restricted. Several guidelines have been issued by major professional organizations, including the International Society of Ultrasound in Obstetrics and Gynecology and the Society for Maternal-Fetal Medicine. The differences in recommendations, in particular about Doppler velocimetry of the ductus venosus and middle cerebral artery, have created confusion among clinicians, and this review has intended to clarify and highlight the available evidence that is pertinent to clinical management. A fetus who is small for gestational age is …

Genetic Subtyping And Phenotypic Characterization Of The Immune Microenvironment And Myc/Bcl2 Double Expression Reveal Heterogeneity In Diffuse Large B-Cell Lymphoma, Zijun Y Xu-Monette, Li Wei, Xiaosheng Fang, Qingyan Au, Harry Nunns, Máté Nagy, Alexandar Tzankov, Feng Zhu, Carlo Visco, Govind Bhagat, Karen Dybkaer, April Chiu, Wayne Tam, Youli Zu, Eric D Hsi, Fredrick B Hagemeister, Xiaoping Sun, Xin Han, Heounjeong Go, Maurilio Ponzoni, Andrés J M Ferreri, Michael B Møller, Benjamin M Parsons, J Han Van Krieken, Miguel A Piris, Jane N Winter, Yong Li, Bing Xu, Maher Albitar, Hua You, Ken H Young

Faculty, Staff and Students Publications

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers.

EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of …

The Association Between Rest-Activity Rhythms And Glycemic Markers: The Us National Health And Nutrition Examination Survey, 2011-2014, Qian Xiao, Charles E Matthews, Mary Playdon, Cici Bauer

Faculty, Staff and Student Publications

OBJECTIVES: Previous studies conducted in mostly homogeneous sociodemographic samples have reported a relationship between weakened and/or disrupted rest-activity patterns and metabolic dysfunction. This study aims to examine rest-activity rhythm characteristics in relation to glycemic markers in a large nationally representative and diverse sample of American adults.

METHODS: This study used data from the National Health and Nutrition Examination Survey 2011-2014. Rest-activity characteristics were derived from extended cosine models using 24-hour actigraphy. We used multinomial logistic regression and multiple linear regression models to assess the associations with multiple glycemic markers (i.e., glycated hemoglobin, fasting glucose and insulin, homeostatic model assessment of …

Reducing Influenza Virus Transmission: The Potential Value Of Antiviral Treatment, Frederick G Hayden, Jason Asher, Benjamin J Cowling, Aeron C Hurt, Hideyuki Ikematsu, Klaus Kuhlbusch, Annabelle Lemenuel-Diot, Zhanwei Du, Lauren Ancel Meyers, Pedro A Piedra, Takahiro Takazono, Hui-Ling Yen, Arnold S Monto

Faculty, Staff and Students Publications

Prompt antiviral treatment has the potential to reduce influenza virus transmission to close contacts, but rigorous data on the magnitude of treatment effects on transmission are limited. Animal model data indicate that rapid reductions in viral replication after antiviral treatment reduce the risk of transmission. Observational and clinical trial data with oseltamivir and other neuraminidase inhibitors indicate that prompt treatment of household index patients seems to reduce the risk of illness in contacts, although the magnitude of the reported effects has varied widely across studies. In addition, the potential risk of transmitting drug-resistant variants exists with all approved classes of …

Multiple Approaches Converge On Three Biological Subtypes Of Meningioma And Extract New Insights From Published Studies, James C Bayley, Caroline C Hadley, Arif O Harmanci, Akdes S Harmanci, Tiemo J Klisch, Akash J Patel

Faculty, Staff and Student Publications

One-fifth of meningiomas classified as benign by World Health Organization (WHO) histopathological grading will behave malignantly. To better diagnose these tumors, several groups turned to DNA methylation, whereas we combined RNA-sequencing (RNA-seq) and cytogenetics. Both approaches were more accurate than histopathology in identifying aggressive tumors, but whether they revealed similar tumor types was unclear. We therefore performed unbiased DNA methylation, RNA-seq, and cytogenetic profiling on 110 primary meningiomas WHO grade I and II). Each technique distinguished the same three groups (two benign and one malignant) as our previous molecular classification; integrating these methods into one classifier further improved accuracy. Computational …

Coronavirus Disease 2019 (Covid-19) Research Agenda For Healthcare Epidemiology, Lona Mody, Hilary M Babcock, Jennie H Kwon, Et Al

Open Access Publications

This SHEA white paper identifies knowledge gaps and challenges in healthcare epidemiology research related to coronavirus disease 2019 (COVID-19) with a focus on core principles of healthcare epidemiology. These gaps, revealed during the worst phases of the COVID-19 pandemic, are described in 10 sections: epidemiology, outbreak investigation, surveillance, isolation precaution practices, personal protective equipment (PPE), environmental contamination and disinfection, drug and supply shortages, antimicrobial stewardship, healthcare personnel (HCP) occupational safety, and return to work policies. Each section highlights three critical healthcare epidemiology research questions with detailed description provided in supplementary materials. This research agenda calls for translational studies from laboratory-based …

Construction And Validation Of Prognostic Nomogram For Metaplastic Breast Cancer, Yongfeng Li, Daobao Chen, Haojun Xuan, Mihnea P Dragomir, George A Calin, Xuli Meng, Meng Chen, Hongchuan Jin

Faculty, Staff and Student Publications

In this study we aimed to develop nomogram models for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with metaplastic breast cancer (MBC). Data of patients diagnosed with MBC from 1973 to 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to identify independent prognostic factors for OS and CSS of MBC patients. The obtained prognostic variables were combined to construct nomogram models for predicting OS and CSS in patients with MBC. Model performance was evaluated using concordance index (C-index) and calibration plots. Data from 1125 patients …

A Mechanistic Modeling Framework Reveals The Key Principles Underlying Tumor Metabolism, Shubham Tripathi, Jun Hyoung Park, Shivanand Pudakalakatti, Pratip K Bhattacharya, Benny Abraham Kaipparettu, Herbert Levine

Faculty, Staff and Student Publications

While aerobic glycolysis, or the Warburg effect, has for a long time been considered a hallmark of tumor metabolism, recent studies have revealed a far more complex picture. Tumor cells exhibit widespread metabolic heterogeneity, not only in their presentation of the Warburg effect but also in the nutrients and the metabolic pathways they are dependent on. Moreover, tumor cells can switch between different metabolic phenotypes in response to environmental cues and therapeutic interventions. A framework to analyze the observed metabolic heterogeneity and plasticity is, however, lacking. Using a mechanistic model that includes the key metabolic pathways active in tumor cells, …

Recent Progress In Biopolymer-Based Hydrogel Materials For Biomedical Applications., Ayaz Mahmood, Dev Patel, Brandon Hickson, John Desrochers, Xiao Hu

College of Science & Mathematics Departmental Research

Hydrogels from biopolymers are readily synthesized, can possess various characteristics for different applications, and have been widely used in biomedicine to help with patient treatments and outcomes. Polysaccharides, polypeptides, and nucleic acids can be produced into hydrogels, each for unique purposes depending on their qualities. Examples of polypeptide hydrogels include collagen, gelatin, and elastin, and polysaccharide hydrogels include alginate, cellulose, and glycosaminoglycan. Many different theories have been formulated to research hydrogels, which include Flory-Rehner theory, Rubber Elasticity Theory, and the calculation of porosity and pore size. All these theories take into consideration enthalpy, entropy, and other thermodynamic variables so that …

New Approaches For Testing Non-Inferiority For Three-Arm Trials With Poisson Distributed Outcomes, Samiran Ghosh, Erina Paul, Shrabanti Chowdhury, Ram C Tiwari

Faculty, Staff and Student Publications

With the availability of limited resources, innovation for improved statistical method for the design and analysis of randomized controlled trials (RCTs) is of paramount importance for newer and better treatment discovery for any therapeutic area. Although clinical efficacy is almost always the primary evaluating criteria to measure any beneficial effect of a treatment, there are several important other factors (e.g., side effects, cost burden, less debilitating, less intensive, etc.), which can permit some less efficacious treatment options favorable to a subgroup of patients. This leads to non-inferiority (NI) testing. The objective of NI trial is to show that an experimental …

Accuracy And Practical Considerations For Doubly Labeled Water Analysis In Nutrition Studies Using A Laser-Based Isotope Instrument (Off-Axis Integrated Cavity Output Spectroscopy), Linda M Reynard, William W Wong, Noreen Tuross

Children’s Nutrition Research Center Staff Publications

Background: Given the utility of the doubly labeled water (DLW) method for determination of energy expenditure, additional techniques for isotope analysis of the samples are welcome. Laser-based instruments are one such new analytical tool, but their accuracy and feasibility for DLW studies are grossly understudied.

Objectives: We assessed the accuracy of laser-based isotope ratio measurements as part of the DLW method for estimation of carbon dioxide production rate (rCO2) and total energy expenditure (TEE), in between-group comparison study designs.

Methods: Urine samples from a previous study were analyzed with a laser-based instrument [off-axis integrated cavity output spectroscopy (OA-ICOS)]. In that …

Pressure-Mediated Reflection Spectroscopy Criterion Validity As A Biomarker Of Fruit And Vegetable Intake: A 2-Site Cross-Sectional Study Of 4 Racial Or Ethnic Groups, Stephanie B Jilcott Pitts, Nancy E Moran, Qiang Wu, Lisa Harnack, Neal E Craft, Neil Hanchard, Ronny Bell, Stacey G Moe, Nevin Johnson, Justice Obasohan, Pamela L Carr-Manthe, Melissa N Laska

Children’s Nutrition Research Center Staff Publications

Background: Valid biomarkers of fruit and vegetable (FV) intake are needed for field-based nutrition research.

Objectives: To examine criterion-related validity of pressure-mediated reflection spectroscopy as a proxy measure of FV intake, using plasma carotenoids and self-reported FV and carotenoid intake as primary and secondary criterion measures, respectively.

Methods: Healthy adults 18-65 y of age, self-identifying as African American/black (n = 61), Asian (n = 53), white (n = 70), or Hispanic (n = 29), in North Carolina and Minnesota were recruited. Skin carotenoids were assessed via pressure-mediated reflection spectroscopy (Veggie Meter), skin melanin via spectrophotometer, and total plasma carotenoid concentration …

Lncrnafunc: A Knowledgebase Of Lncrna Function In Human Cancer, Mengyuan Yang, Huifen Lu, Jiajia Liu, Sijia Wu, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

The long non-coding RNAs associating with other molecules can coordinate several physiological processes and their dysfunction can impact diverse human diseases. To date, systematic and intensive annotations on diverse interaction regulations of lncRNAs in human cancer were not available. Here, we built lncRNAfunc, a knowledgebase of lncRNA function in human cancer at https://ccsm.uth.edu/lncRNAfunc, aiming to provide a resource and reference for providing therapeutically targetable lncRNAs and intensive interaction regulations. To do this, we collected 15 900 lncRNAs across 33 cancer types from TCGA. For individual lncRNAs, we performed multiple interaction analyses of different biomolecules including DNA, RNA, and protein levels. …

Fusiongdb 20: Fusion Gene Annotation Updates Aided By Deep Learning, Pora Kim, Hua Tan, Jiajia Liu, Haeseung Lee, Hyesoo Jung, Himanshu Kumar, Xiaobo Zhou

Faculty, Staff and Student Publications

A knowledgebase of the systematic functional annotation of fusion genes is critical for understanding genomic breakage context and developing therapeutic strategies. FusionGDB is a unique functional annotation database of human fusion genes and has been widely used for studies with diverse aims. In this study, we report fusion gene annotation updates aided by deep learning (FusionGDB 2.0) available at https://compbio.uth.edu/FusionGDB2/. FusionGDB 2.0 has substantial updates of contents such as up-to-date human fusion genes, fusion gene breakage tendency score with FusionAI deep learning model based on 20 kb DNA sequence around BP, investigation of overlapping between fusion breakpoints with 44 human …

Effect Of Aerobic Or Resistance Exercise, Or Both, On Intermuscular And Visceral Fat And Physical And Metabolic Function In Older Adults With Obesity While Dieting, Debra L Waters, Lina Aguirre, Burke Gurney, David R Sinacore, Kenneth Fowler, Giulia Gregori, Reina Armamento-Villareal, Clifford Qualls, Dennis T Villareal

2020-Current year OA Pubs

BACKGROUND: Obesity exacerbates age-related effects on body composition and physical and metabolic function. Which exercise mode is most effective in mitigating these deleterious changes in dieting older adults with obesity is unknown.

METHODS: In a randomized controlled trial, we performed a head-to-head comparison of aerobic (AEX), resistance (REX), or combination (COMB) exercise during matched ~10% weight loss in 160 obese older adults. Prespecified analyses compared 6-month changes in intermuscular adipose tissue (IMAT) and visceral adipose tissue (VAT) assessed using MRI, insulin sensitivity index (ISI) by oral glucose tolerance test, physical function using Modified Physical Performance Test (PPT), VO2peak, gait speed, …

Sensei: How Many Samples To Tell A Change In Cell Type Abundance?, Shaoheng Liang, Jason Willis, Jinzhuang Dou, Vakul Mohanty, Yuefan Huang, Eduardo Vilar, Ken Chen

Faculty, Staff and Student Publications

Cellular heterogeneity underlies cancer evolution and metastasis. Advances in single-cell technologies such as single-cell RNA sequencing and mass cytometry have enabled interrogation of cell type-specific expression profiles and abundance across heterogeneous cancer samples obtained from clinical trials and preclinical studies. However, challenges remain in determining sample sizes needed for ascertaining changes in cell type abundances in a controlled study. To address this statistical challenge, we have developed a new approach, named Sensei, to determine the number of samples and the number of cells that are required to ascertain such changes between two groups of samples in single-cell studies. Sensei expands …

Quantification Of Infarct Core Signal Using Ct Imaging In Acute Ischemic Stroke, Uma Maria Lal-Trehan Estrada, Grant Meeks, Sergio Salazar-Marioni, Fabien Scalzo, Mudassir Farooqui, Juan Vivanco-Suarez, Santiago Ortega Gutierrez, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

In stroke care, the extent of irreversible brain injury, termed infarct core, plays a key role in determining eligibility for acute treatments, such as intravenous thrombolysis and endovascular reperfusion therapies. Many of the pivotal randomized clinical trials testing those therapies used MRI Diffusion-Weighted Imaging (DWI) or CT Perfusion (CTP) to define infarct core. Unfortunately, these modalities are not available 24/7 outside of large stroke centers. As such, there is a need for accurate infarct core determination using faster and more widely available imaging modalities including Non-Contrast CT (NCCT) and CT Angiography (CTA). Prior studies have suggested that CTA provides improved …

Brain Antigens Stimulate Proliferation Of T Lymphocytes With A Pathogenic Phenotype In Multiple Sclerosis Patients, Assaf Gottlieb, Hoai Phuong T Pham, John William Lindsey

Faculty, Staff and Student Publications

A method to stimulate T lymphocytes with a broad range of brain antigens would facilitate identification of the autoantigens for multiple sclerosis and enable definition of the pathogenic mechanisms important for multiple sclerosis. In a previous work, we found that the obvious approach of culturing leukocytes with homogenized brain tissue does not work because the brain homogenate suppresses antigen-specific lymphocyte proliferation. We now report a method that substantially reduces the suppressive activity. We used this non-suppressive brain homogenate to stimulate leukocytes from multiple sclerosis patients and controls. We also stimulated with common viruses for comparison. We measured proliferation, selected the …

Deep Graph Convolutional Network For Us Birth Data Harmonization, Lishan Yu, Hamisu M Salihu, Deepa Dongarwar, Luyao Chen, Xiaoqian Jiang

Faculty, Staff and Student Publications

In this paper, we developed a feasible and efficient deep-learning-based framework to combine the United States (US) natality data for the last five decades, with changing variables and factors, into a consistent database. We constructed a graph based on the property and elements of databases, including variables, and conducted a graph convolutional network (GCN) to learn the embeddings of variables on the constructed graph, where the learned embeddings implied the similarity of variables. Specifically, we devised a loss function with a slack margin and a banlist mechanism (for a random walk) to learn the desired structure (two nodes sharing more …

Temporal Cohort Logic, Guo-Qiang Zhang, Xiaojin Li, Yan Huang, Licong Cui

Faculty, Staff and Student Publications

We introduce a new logic, called Temporal Cohort Logic (TCL), for cohort specification and discovery in clinical and population health research. TCL is created to fill a conceptual gap in formalizing temporal reasoning in biomedicine, in a similar role that temporal logics play for computer science and its applications. We provide formal syntax and semantics for TCL and illustrate the various logical constructs using examples related to human health. Relationships and distinctions with existing temporal logical frameworks are discussed. Applications in electronic health record (EHR) and in neurophysiological data resource are provided. Our approach differs from existing temporal logics, in …

Racial And Socioeconomic Disparities In Patients With Meningioma: A Retrospective Cohort Study, Hudin N Jackson, Caroline C Hadley, A Basit Khan, Ron Gadot, James C Bayley, Arya Shetty, Jacob Mandel, Ali Jalali, K Kelly Gallagher, Alex D Sweeney, Arif O Harmanci, Akdes S Harmanci, Tiemo Klisch, Shankar P Gopinath, Ganesh Rao, Daniel Yoshor, Akash J Patel

Faculty, Staff and Student Publications

BACKGROUND: Meningiomas are the most common intracranial neoplasms. Although genomic analysis has helped elucidate differences in survival, there is evidence that racial disparities may influence outcomes. African Americans have a higher incidence of meningiomas and poorer survival outcomes. The etiology of these disparities remains unclear, but may include a combination of pathophysiology and other factors.

OBJECTIVE: To determine factors that contribute to different clinical outcomes in racial populations.

METHODS: We retrospectively reviewed 305 patients who underwent resection for meningiomas at a single tertiary care facility. We used descriptive statistics and univariate, multivariable, and Kaplan-Meier analyses to study clinical, radiographical, and …

Risk Of Alzheimer's Disease Following Influenza Vaccination: A Claims-Based Cohort Study Using Propensity Score Matching, Avram S Bukhbinder, Yaobin Ling, Omar Hasan, Xiaoqian Jiang, Yejin Kim, Kamal N Phelps, Rosemarie E Schmandt, Albert Amran, Ryan Coburn, Srivathsan Ramesh, Qian Xiao, Paul E Schulz

Faculty, Staff and Student Publications

BACKGROUND: Prior studies have found a reduced risk of dementia of any etiology following influenza vaccination in selected populations, including veterans and patients with serious chronic health conditions. However, the effect of influenza vaccination on Alzheimer's disease (AD) risk in a general cohort of older US adults has not been characterized.

OBJECTIVE: To compare the risk of incident AD between patients with and without prior influenza vaccination in a large US claims database.

METHODS: Deidentified claims data spanning September 1, 2009 through August 31, 2019 were used. Eligible patients were free of dementia during the 6-year look-back period and≥65 years …

Fairly Predicting Graft Failure In Liver Transplant For Organ Assigning, Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

Liver transplant is an essential therapy performed for severe liver diseases. The fact of scarce liver resources makes the organ assigning crucial. Model for End-stage Liver Disease (MELD) score is a widely adopted criterion when making organ distribution decisions. However, it ignores post-transplant outcomes and organ/donor features. These limitations motivate the emergence of machine learning (ML) models. Unfortunately, ML models could be unfair and trigger bias against certain groups of people. To tackle this problem, this work proposes a fair machine learning framework targeting graft failure prediction in liver transplant. Specifically, knowledge distillation is employed to handle dense and sparse …

Facilitating Federated Genomic Data Analysis By Identifying Record Correlations While Ensuring Privacy, Leonard Dervishi, Xinyue Wang, Wentao Li, Anisa Halimi, Jaideep Vaidya, Xiaoqian Jiang, Erman Ayday

Faculty, Staff and Student Publications

With the reduction of sequencing costs and the pervasiveness of computing devices, genomic data collection is continually growing. However, data collection is highly fragmented and the data is still siloed across different repositories. Analyzing all of this data would be transformative for genomics research. However, the data is sensitive, and therefore cannot be easily centralized. Furthermore, there may be correlations in the data, which if not detected, can impact the analysis. In this paper, we take the first step towards identifying correlated records across multiple data repositories in a privacy-preserving manner. The proposed framework, based on random shuffling, synthetic record …

Caries Risk Documentation And Prevention: Emeasures For Dental Electronic Health Records, Suhasini Bangar, Ana Neumann, Joel M White, Alfa Yansane, Todd R Johnson, Gregory W Olson, Shwetha V Kumar, Krishna K Kookal, Aram Kim, Enihomo Obadan-Udoh, Elizabeth Mertz, Kristen Simmons, Joanna Mullins, Ryan Brandon, Muhammad F Walji, Elsbeth Kalenderian

Faculty, Staff and Student Publications

BACKGROUND: Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures).

OBJECTIVE: We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year.

METHODS: Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For …

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, And Beyond, Robert El-Kareh, Dean F Sittig

Faculty, Staff and Student Publications

Patient care in intensive care environments is complex, time-sensitive, and data-rich, factors that make these settings particularly well-suited to clinical decision support (CDS). A wide range of CDS interventions have been used in intensive care unit environments. The field needs well-designed studies to identify the most effective CDS approaches. Evolving artificial intelligence and machine learning models may reduce information-overload and enable teams to take better advantage of the large volume of patient data available to them. It is vital to effectively integrate new CDS into clinical workflows and to align closely with the cognitive processes of frontline clinicians.

Automated Identification Of Missing Is-A Relations In The Human Phenotype Ontology, Maryamsadat Mohtashamian, Ran Hu, Rashmie Abeysinghe, Xubing Hao, Hua Xu, Licong Cui

Faculty, Staff and Student Publications

Auditing the Human Phenotype Ontology (HPO) is necessary to provide accurate terminology for its use in clinical research. We investigate an approach leveraging the lexical features of concepts in HPO to identify missing IS-A relations among HPO concepts. We first model the names of HPO concepts as sets of words in lower case. Then, we generate two types of concept-pairs which have at least a single common word: (1) Linked concept-pairs generated from concept-pairs having an IS-A relation; (2) Unlinked concept-pairs generated from concept-pairs without an IS- A relation. Concept-pairs generate Derived Term Pairs (DTPs) emphasizing unique lexical information of …

Cost Of Care For Asylum Seekers And Refugees Entering The United States: The Case Of Volunteer Medical Providers In El Paso, Texas, Rigoberto I Delgado, Manuel De La Rosa, Marlon A Picado, Lisa Ayoub-Rodriguez, Celia E Gonzalez, Leopold Gemoets

Faculty, Staff and Student Publications

BACKGROUND: Between October 2018, and February 2020, the United States saw an unprecedented increase in the number of asylum seekers and refugees arriving unexpectedly at international crossings along the US-Mexico Border. Many of these migrants needed proper medical attention, and consequently created significant pressure on local health systems. In El Paso, Texas, volunteer clinicians, collaborating closely with religious organizations and non-governmental organizations, provided outpatient medical care for the new arrivals; the county hospital provided in-patient care at local tax payers' expense. The objective of this study was to estimate costs of healthcare services offered by these volunteers in order to …