Data Science Commons^™

Identifying Sleep-Related Factors Associated With Cognitive Function In A Hispanics/Latinos Cohort: A Dual Random Forest Approach, Li Xiaojin, Cui Licong, Wang Fei, Paul E Schulz, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Disordered sleep is associated with poor cognitive function and cognitive decline. However, little is known regarding the association of sleep-related factors with cognitive function in underrepresented cohorts such as the Hispanic/Latino population. Leveraging the National Sleep Research Resource, one of the most comprehensive collections of sleep studies, we identified a Hispanic/Latino cohort of 1,031 lower cognitive function cases and 2,062 normal controls. We developed a novel dual random forest (DRF) approach to discriminate cases against controls for estimating the potential impact of sleep-related variables related to the decline of cognitive function. Several important sleep-related factors were identified which may be …

Representation Of Ehr Data For Predictive Modeling: A Comparison Between Umls And Other Terminologies, Laila Rasmy, Firat Tiryaki, Yujia Zhou, Yang Xiang, Cui Tao, Hua Xu, Degui Zhi

Faculty, Staff and Student Publications

OBJECTIVE: Predictive disease modeling using electronic health record data is a growing field. Although clinical data in their raw form can be used directly for predictive modeling, it is a common practice to map data to standard terminologies to facilitate data aggregation and reuse. There is, however, a lack of systematic investigation of how different representations could affect the performance of predictive models, especially in the context of machine learning and deep learning.

MATERIALS AND METHODS: We projected the input diagnoses data in the Cerner HealthFacts database to Unified Medical Language System (UMLS) and 5 other terminologies, including CCS, CCSR, …

Covid-19 Testnorm: A Tool To Normalize Covid-19 Testing Names To Loinc Codes, Xiao Dong, Jianfu Li, Ekin Soysal, Jiang Bian, Scott L Duvall, Elizabeth Hanchrow, Hongfang Liu, Kristine E Lynch, Michael Matheny, Karthik Natarajan, Lucila Ohno-Machado, Serguei Pakhomov, Ruth Madeleine Reeves, Amy M Sitapati, Swapna Abhyankar, Theresa Cullen, Jami Deckard, Xiaoqian Jiang, Robert Murphy, Hua Xu

Faculty, Staff and Student Publications

Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) …

Deep Learning In Clinical Natural Language Processing: A Methodical Review, Stephen Wu, Kirk Roberts, Surabhi Datta, Jingcheng Du, Zongcheng Ji, Yuqi Si, Sarvesh Soni, Qiong Wang, Qiang Wei, Yang Xiang, Bo Zhao, Hua Xu

Faculty, Staff and Student Publications

OBJECTIVE: This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.

MATERIALS AND METHODS: We searched MEDLINE, EMBASE, Scopus, the Association for Computing Machinery Digital Library, and the Association for Computational Linguistics Anthology for articles using DL-based approaches to NLP problems in electronic health records. After screening 1,737 articles, we collected data on 25 variables across 212 papers.

RESULTS: DL in clinical NLP publications more than doubled each year, through 2018. Recurrent neural networks (60.8%) …

Digilego For Peripartum Depression: A Novel Patient-Facing Digital Health Instantiation, J Rodin, C Timko, S Harris

Faculty, Staff and Student Publications

Digital health technologies offer unique opportunities to improve health outcomes for mental health conditions such as peripartum depression (PPD), a disorder that affects approximately 10-15% of women in the U.S. every year. In this paper, we present the adaption of a digital technology development framework, Digilego, in the context of PPD. Methods include mapping of the Behavior Intervention Technology (BIT) model and the Patient Engagement Framework (PEF) to translate patient needs captured through focus groups. This informs formative development and implementation of digital health features for optimal patient engagement in PPD screening and management. Results show an array ofPPD-specific Digilego …

Causal Discovery In Radiographic Markers Of Knee Osteoarthritis And Prediction For Knee Osteoarthritis Severity With Attention-Long Short-Term Memory, Yanfei Wang, Lei You, Jacqueline Chyr, Lan Lan, Weiling Zhao, Yujia Zhou, Hua Xu, Philip Noble, Xiaobo Zhou

Faculty, Staff and Student Publications

The goal of this study is to build a prognostic model to predict the severity of radiographic knee osteoarthritis (KOA) and to identify long-term disease progression risk factors for early intervention and treatment. We designed a long short-term memory (LSTM) model with an attention mechanism to predict Kellgren/Lawrence (KL) grade for knee osteoarthritis patients. The attention scores reveal a time-associated impact of different variables on KL grades. We also employed a fast causal inference (FCI) algorithm to estimate the causal relation of key variables, which will aid in clinical interpretability. Based on the clinical information of current visits, we accurately …

Enhancing Clinical Concept Extraction With Contextual Embeddings, Yuqi Si, Jingqi Wang, Hua Xu, Kirk Roberts

Faculty, Staff and Student Publications

OBJECTIVE: Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Recently, however, more advanced embedding methods and representations (eg, ELMo, BERT) have further pushed the state of the art in NLP, yet there are no common best practices for how to integrate these representations into clinical tasks. The purpose of this study, then, is to explore the space of possible options in utilizing these new models for clinical concept extraction, including comparing these to traditional word embedding methods (word2vec, GloVe, fastText).

MATERIALS AND METHODS: Both off-the-shelf, open-domain embeddings and …

Effects Of A Community Population Health Initiative On Blood Pressure Control In Latinos, James R Langabeer, Timothy D Henry, Carlos Perez Aldana, Larissa Deluna, Nora Silva, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

Background Hypertension remains one of the most important, modifiable cardiovascular risk factors. Yet, the largest minority ethnic group (Hispanics/Latinos) often have different health outcomes and behavior, making hypertension management more difficult. We explored the effects of an American Heart Association-sponsored population health intervention aimed at modifying behavior of Latinos living in Texas. Methods and Results We enrolled 8071 patients, and 5714 (65.7%) completed the 90-day program (58.5 years ±11.7; 59% female) from July 2016 to June 2018. Navigators identified patients with risk factors; initial and final blood pressure ( BP ) readings were performed in the physician's office; and interim …

A Frame-Based Nlp System For Cancer-Related Information Extraction, Yuqi Si, Kirk Roberts

Faculty, Staff and Student Publications

We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. The system consists of two constituent sequence classifiers: a frame identification (lexical unit) classifier and a frame element classifier. The classifier achieves an F

Clinical Decision Support Capabilities Of Commercially-Available Clinical Information Systems, Adam Wright, Dean F Sittig, Joan S Ash, Sapna Sharma, Justine E Pang, Blackford Middleton

Faculty, Staff and Student Publications

BACKGROUND: The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems.

METHODS: The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features.

RESULTS: Six of the nine reviewed systems offered all the applicable …

Improving Clinical Quality Indicators Through Electronic Health Records: It Takes More Than Just A Reminder, Dean F Sittig, Jonathan M Teich, Jerome A Osheroff, Hardeep Singh

Faculty, Staff and Student Publications

No abstract provided.

Taxonomy Development And Knowledge Representation Of Nurses' Personal Cognitive Artifacts, Sharon Mclane, James P Turley

Faculty, Staff and Student Publications

Nurses prepare knowledge representations, or summaries of patient clinical data, each shift. These knowledge representations serve multiple purposes, including support of working memory, workload organization and prioritization, critical thinking, and reflection. This summary is integral to internal knowledge representations, working memory, and decision-making. Study of this nurse knowledge representation resulted in development of a taxonomy of knowledge representations necessary to nursing practice.This paper describes the methods used to elicit the knowledge representations and structures necessary for the work of clinical nurses, described the development of a taxonomy of this knowledge representation, and discusses translation of this methodology to the cognitive …

Improving Follow-Up Of Abnormal Cancer Screens Using Electronic Health Records: Trust But Verify Test Result Communication, Hardeep Singh, Lindsey Wilson, Laura A Petersen, Mona K Sawhney, Brian Reis, Donna Espadas, Dean F Sittig

Faculty, Staff and Student Publications

BACKGROUND: Early detection of colorectal cancer through timely follow-up of positive Fecal Occult Blood Tests (FOBTs) remains a challenge. In our previous work, we found 40% of positive FOBT results eligible for colonoscopy had no documented response by a treating clinician at two weeks despite procedures for electronic result notification. We determined if technical and/or workflow-related aspects of automated communication in the electronic health record could lead to the lack of response.

METHODS: Using both qualitative and quantitative methods, we evaluated positive FOBT communication in the electronic health record of a large, urban facility between May 2008 and March 2009. …

Sustained Attention In Children With Two Etiologies Of Early Hydrocephalus, Maegan D. Swartwout, Paul T. Cirino, Amy W. Hampson, Jack M. Fletcher, Michael E. Brandt, Maureen Dennis

Faculty, Staff and Student Publications

Several studies have shown that children with spina bifida meningomyelocele (SBM) and hydrocephalus have attention problems on parent ratings and difficulties in stimulus orienting associated with a posterior brain attention system. Less is known about response control and inhibition associated with an anterior brain attention system. Using the Gordon Vigilance Task (Gordon, 1983), we studied error rate, reaction time, and performance over time for sustained attention, a key anterior attention function, in 101 children with SBM, 17 with aqueductal stenosis (AS; another condition involving congenital hydrocephalus), and 40 typically developing controls (NC). In SBM, we investigated the relation between cognitive …

Effect Of Progressive Mandibular Advancement On Pharyngeal Airway Size In Anesthetized Adults, Samuel T Kuna, Lee C Woodson, Daneshvari R Solanki, Oliver Esch, Donald E Frantz, Mali Mathru

Faculty, Staff and Student Publications

BACKGROUND: General anesthesia in adult humans is associated with narrowing or complete closure of the pharyngeal airway. The purpose of this study was to determine the effect of progressive mandibular advancement on pharyngeal airway size in normal adults during intravenous infusion of propofol for anesthesia.

METHODS: Magnetic resonance imaging was performed in nine normal adults during wakefulness and during propofol anesthesia. A commercially available intraoral appliance was used to manually advance the mandible. Images were obtained during wakefulness without the appliance and during anesthesia with the participants wearing the appliance under three conditions: without mandibular advancement, advancement to 50% maximum …

Molecular And Macromolecular Alterations Of Recombinant Adenoviral Vectors Do Not Resolve Changes In Hepatic Drug Metabolism During Infection, Shellie M Callahan, Piyanuch Wonganan, Maria A Croyle

Faculty, Staff and Student Publications

In this report we test the hypothesis that long-term virus-induced alterations in CYP occur from changes initiated by the virus that may not be related to the immune response. Enzyme activity, protein expression and mRNA of CYP3A2, a correlate of human CYP3A4, and CYP2C11, responsive to inflammatory mediators, were assessed 0.25, 1, 4, and 14 days after administration of several different recombinant adenoviruses at a dose of 5.7 x 1012 virus particles (vp)/kg to male Sprague Dawley rats. Wild type adenovirus, containing all viral genes, suppressed CYP3A2 and 2C11 activity by 37% and 39%, respectively within six hours. Levels fell …

Verb Generation In Children With Spina Bifida, Maureen Dennis, Derryn Jewell, Ross Hetherington, Christine Burton, Michael E. Brandt, Susan E. Blaser, Jack M Fletcher

Faculty, Staff and Student Publications

We investigated verb generation in children with spina bifida meningomyelocele (SBM; n = 55) and in typically developing controls (n = 32). Participants completed 6 blocks (40 trials each) of a task requiring them to produce a semantically related verb in response to a target noun and an additional 40 trials on which they were simply required to read target nouns aloud. After controlling for reading response time, groups did not differ significantly in verb generation response time or learning. Children with SBM produced more non-verb errors than controls and tended to repeat their mistakes over blocks. Verb generation performance …

Focal White Matter Changes In Spasmodic Dysphonia: A Combined Diffusion Tensor Imaging And Neuropathological Study, Kristina Simonyan, Fernanda Tovar-Moll, John Ostuni, Mark Hallett, Victor F Kalasinsky, Michael R Lewin-Smith, Elisabeth J Rushing, Alexander O Vortmeyer, Christy L Ludlow

Faculty, Staff and Student Publications

Spasmodic dysphonia is a neurological disorder characterized by involuntary spasms in the laryngeal muscles during speech production. Although the clinical symptoms are well characterized, the pathophysiology of this voice disorder is unknown. We describe here, for the first time to our knowledge, disorder-specific brain abnormalities in these patients as determined by a combined approach of diffusion tensor imaging (DTI) and postmortem histopathology. We used DTI to identify brain changes and to target those brain regions for neuropathological examination. DTI showed right-sided decrease of fractional anisotropy in the genu of the internal capsule and bilateral increase of overall water diffusivity in …

Searching For The Majority: Algorithms Of Voluntary Control, Jin Fan, Kevin G. Guise, Xun Liu, Hongbin Wang

Faculty, Staff and Student Publications

Voluntary control of information processing is crucial to allocate resources and prioritize the processes that are most important under a given situation; the algorithms underlying such control, however, are often not clear. We investigated possible algorithms of control for the performance of the majority function, in which participants searched for and identified one of two alternative categories (left or right pointing arrows) as composing the majority in each stimulus set. We manipulated the amount (set size of 1, 3, and 5) and content (ratio of left and right pointing arrows within a set) of the inputs to test competing hypotheses …

Correlates Of Tobacco Cessation Counseling Among Hispanic Physicians In The Us: A Cross-Sectional Survey Study, Francisco G Soto Mas, Héctor G Balcázar, Julia Valderrama Alberola, Chiehwen Ed Hsu

Faculty, Staff and Student Publications

BACKGROUND: Physician advice is an important motivator for attempting to stop smoking. However, physicians' lack of intervention with smokers has only modestly improved in the last decade. Although the literature includes extensive research in the area of the smoking intervention practices of clinicians, few studies have focused on Hispanic physicians. The purpose of this study was to explore the correlates of tobacco cessation counseling practices among Hispanic physicians in the US. METHODS: Data were collected through a validated survey instrument among a cross-sectional sample of self-reported Hispanic physicians practicing in New Mexico, and who were members of the New Mexico …

Downregulation Of Rap1gap Contributes To Ras Transformation, Oxana Tsygankova, Gregory V. Prendergast, Kanchan Puttaswamy, Yan Wang, Michael D. Feldman, Hongbin Wang, Marcia S. Brose, Judy L. Meinkoth

Faculty, Staff and Student Publications

Although abundant in well-differentiated rat thyroid cells, Rap1GAP expression was extinguished in a subset of human thyroid tumor-derived cell lines. Intriguingly, Rap1GAP was downregulated selectively in tumor cell lines that had acquired a mesenchymal morphology. Restoring Rap1GAP expression to these cells inhibited cell migration and invasion, effects that were correlated with the inhibition of Rap1 and Rac1 activity. The reexpression of Rap1GAP also inhibited DNA synthesis and anchorage-independent proliferation. Conversely, eliminating Rap1GAP expression in rat thyroid cells induced a transient increase in cell number. Strikingly, Rap1GAP expression was abolished by Ras transformation. The downregulation of Rap1GAP by Ras required the …

Quality Of Weight Loss Advice On Internet Forums, Kevin O Hwang, Kiran Farheen, Craig W Johnson, Eric J Thomas, Ann S Barnes, Elmer V Bernstam

Faculty, Staff and Student Publications

BACKGROUND: Adults use the Internet for weight loss information, sometimes by participating in discussion forums. Our purpose was to analyze the quality of advice exchanged on these forums. METHODS: This was a retrospective analysis of messages posted to 18 Internet weight loss forums during 1 month in 2006. Advice was evaluated for congruence with clinical guidelines; potential for causing harm; and subsequent correction when it was contradictory to guidelines (erroneous) or potentially harmful. Message- and forum-specific characteristics were evaluated as predictors of advice quality and self-correction. RESULTS: Of 3368 initial messages, 266 (7.9%) were requests for advice. Of 654 provisions …

Computer Simulation Of Glioma Growth And Morphology, Hermann B. Frieboes, John S Lowengrub, S Wise, X Zheng, Paul Macklin, Elaine L. Bearer, Vittorio Cristini

Faculty, Staff and Student Publications

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques …

Predictive Oncology: A Review Of Multidisciplinary, Multiscale In Silico Modeling Linking Phenotype, Morphology And Growth, Sandeep Sanga, Hermann B. Frieboes, Xiaoming Zheng, Robert Gatenby, Elaine L. Bearer, Vittorio Cristini

Faculty, Staff and Student Publications

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable …

Exploration Of Computational Methods For Classification Of Movement Intention During Human Voluntary Movement From Single Trial Eeg, Ou Bai, Peter Lin, Sherry Vorbach, Jiang Li, Steve Furlani, Mark Hallett

Electrical & Computer Engineering Faculty Publications

Objective: To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG).

Methods: Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis …

Accuracy And Self Correction Of Information Received From An Internet Breast Cancer List: Content Analysis, Adol Esquivel, Funda Meric-Bernstam, Elmer V Bernstam

Faculty, Staff and Student Publications

OBJECTIVES: To determine the prevalence of false or misleading statements in messages posted by internet cancer support groups and whether these statements were identified as false or misleading and corrected by other participants in subsequent postings. DESIGN: Analysis of content of postings. SETTING: Internet cancer support group Breast Cancer Mailing List. MAIN OUTCOME MEASURES: Number of false or misleading statements posted from 1 January to 23 April 2005 and whether these were identified and corrected by participants in subsequent postings. RESULTS: 10 of 4600 postings (0.22%) were found to be false or misleading. Of these, seven were identified as false …

Guideview: Structured Multi-Modal Delivery Of Clinical Guidelines, M Sriram Iyengar, Subhajit Sarkar, Kira Bacal, Gregory Defouw, Phyllis Mcculley, Victor Hurst

Faculty, Staff and Student Publications

GuideView is a system designed for structured, multi-modal delivery of clinical guidelines. Clinical instructions are presented simultaneously in voice, text, pictures or video or animations. Users navigate using mouse-clicks and voice commands. An evaluation study performed at a medical simulation laboratory found that voice and video instructions were rated highly.

Persuasive Email Messages For Patient Communication, Muhammad Walji, Kathy Johnson-Throop, Todd Johnson, Elmer Bernstam, Jiajie Zhang

Faculty, Staff and Student Publications

To improve health and reduce costs, we need to encourage patients to make better health care decisions. Since email is widely available, it may be useful for patient-directed interventions. However, we know little about how the contents of an email message can influence a health-related decision. We propose a model to understand how patients may process persuasive email messages.

Predicting Childhood Sexual Or Physical Abuse: A Logistic Regression Geo-Mapping Approach To Prevention, Roland K. Tadoum, Kamila Smolij, Michelle A. Lyn, Craig W. Johnson

Faculty, Staff and Student Publications

This study investigates the degree to which gender, ethnicity, relationship to perpetrator, and geomapped socio-economic factors significantly predict the incidence of childhood sexual abuse, physical abuse and non- abuse. These variables are then linked to geographic identifiers using geographic information system (GIS) technology to develop a geo-mapping framework for child sexual and physical abuse prevention.

Using Technology To Teach Technology: Design And Evaluation Of Bilingual Online Physician Education About Electronic Medical Records, Sarah R. Edmonson, Adol Esquivel, Pallavi Mokkarala, Craig W. Johnson, Cynthia L. Phelps

Faculty, Staff and Student Publications

The "EMR Tutorial" is designed to be a bilingual online physician education environment about electronic medical records. After iterative assessment and redesign, the tutorial was tested in two groups: U.S. physicians and Mexican medical students. Split-plot ANOVA revealed significantly different pre-test scores in the two groups, significant cognitive gains for the two groups overall, and no significant difference in the gains made by the two groups. Users rated the module positively on a satisfaction questionnaire.