Statistics and Probability Commons^™

Diabetes And Its Effect On Abdominal Aortic Aneurysm Growth Rate In Hispanic Patients, Monica Betancourt-Garcia, Kristina Vatcheva, Amrit Thakur, Prateek Gupta, Eugene Postevka, Ricardo Martinez, R. Armour Forse

School of Mathematical & Statistical Sciences Faculty Publications

Background

The growth rate of abdominal aortic aneurysms (AAA) can vary depending on age, baseline diameter, blood pressure, race, and history of smoking. Paradoxically, previous studies show evidence of a protective effect of diabetes on the rate of AAA expansion despite its well-established role in the morbidity and mortality of cardiovascular disease. This study aims to investigate the impact diabetes plays on AAA growth within a Hispanic population.

Methods

Data were collected from patients who were predominantly Mexican-American at a single hospital site. Baseline and follow-up measures for AAA diameter were obtained from serial imaging studies. Demographics, medical history, the …

Fractional Random Weighted Bootstrapping For Classification On Imbalanced Data With Ensemble Decision Tree Methods, Sean Charles Carter

USF Tampa Graduate Theses and Dissertations

Ensemble methods are commonly used for building predictive models for classification. Models that are unstable to perturbations in the training set, such as the decision tree, often see considerable reductions in error when grouped, using bootstrapped resamples of the training data to train many models. The non-parametric bootstrap, however, has limited efficacy when used on severely imbalanced data, especially when the number of observations of one or more classes is exceptionally small. We explore the fractional random weighted bootstrap, which randomly assigns fractional weights to observations, as an alternative resampling pro cedure in training machine learning ensembles, particularly decision tree …

New Measure Of Skewness Of A Probability Distribution, Ashok Singh, Laxmi Gewali, Jiwan Khatiwada

Hospitality Faculty Research

Symmetry of the underlying probability density plays an important role in statistical inference, since the sampling distribution of the sample mean for a given sample size is more likely to be approximately normal for a symmetric distribution than for an asymmetric one. In this article, two new measures of skewness are proposed and the confidence intervals for true skewness are obtained via Monte Carlo simulation experiments. One advantage of the two proposed skewness measures over the standard measures of skewness is that the proposed measures of skewness take values inside the range (-1, +1).

Establishing An Analytics Capability Within Hr, Rizwan Khan

River Cities Industrial and Organizational Psychology Conference

With advancements in technology, HR finally has the tools available to collect and process people data. But is that all that is needed to successfully implement and sustain an analytics capability within HR? The purpose of this presentation/tutorial is to demonstrate a realistic journey The AES Corporation has taken thus far in developing its People Analytics capability. A framework for the implementation of People Analytics will be presented which incorporates themes in I/O Psychology that have been incorporated into the framework such as goal setting theory, job analysis, and change management. How this framework is operationalized will also be demonstrated …

Evaluating The Impact Of Proactive Care Management With Idstrat, D.J. Donahue, Lauren Staples

Published and Grey Literature from PhD Candidates

This purpose of this study is to quantify potential cost savings and member care improvements as a result of engagement through BlueCross BlueShield of Tennessee’s (BCBST) Identification and Stratification (IDStrat) process. Commercial members engaged in clinical management that were identified through IDStrat were compared to commercial members identified through other means across several metrics including per-member, per-month (PMPM) cost and physician visits. Members identified by IDStrat experienced a statistically significant 7% greater reduction in costs after being engaged when compared with those identified by other methods. Members identified by IDStrat also experienced a significant reduction in emergency room visits after …

Inferring A Consensus Problem List Using Penalized Multistage Models For Ordered Data, Philip S. Boonstra, John C. Krauss

The University of Michigan Department of Biostatistics Working Paper Series

A patient's medical problem list describes his or her current health status and aids in the coordination and transfer of care between providers, among other things. Because a problem list is generated once and then subsequently modified or updated, what is not usually observable is the provider-effect. That is, to what extent does a patient's problem in the electronic medical record actually reflect a consensus communication of that patient's current health status? To that end, we report on and analyze a unique interview-based design in which multiple medical providers independently generate problem lists for each of three patient case abstracts …

Population Health Management, Data And Technology, Helena Ladd, Cody Hepp, Anna Mccloud, Hannah Granger, Mary Ellen Hethcox, Samuel Calabrese

Pharmacy and Wellness Review

No abstract provided.

Phase Iv Clinical Trials: Postmarketing Surveillance Of Prescription Drugs, Morgan Belling, Jacquline Nunner, Jessica Stemen

Pharmacy and Wellness Review

No abstract provided.

Enhancing Timeliness Of Drug Overdose Mortality Surveillance: A Machine Learning Approach, Patrick J. Ward, Peter J. Rock, Svetla Slavova, April M. Young, Terry L. Bunn, Ramakanth Kavuluru

Kentucky Injury Prevention and Research Center Faculty Publications

BACKGROUND: Timely data is key to effective public health responses to epidemics. Drug overdose deaths are identified in surveillance systems through ICD-10 codes present on death certificates. ICD-10 coding takes time, but free-text information is available on death certificates prior to ICD-10 coding. The objective of this study was to develop a machine learning method to classify free-text death certificates as drug overdoses to provide faster drug overdose mortality surveillance.

METHODS: Using 2017–2018 Kentucky death certificate data, free-text fields were tokenized and features were created from these tokens using natural language processing (NLP). Word, bigram, and trigram features were created …

I Spy With My Little Eye … A Knee About To Go 'Pop'? Can Coaches And Sports Medicine Professionals Predict Who Is At Greater Risk Of Acl Rupture?, Anne Inger Mørtvedt, Tron Krosshaug, Roald Bahr, Erich Petushek

Michigan Tech Publications, Part 1

BACKGROUND: The vertical drop jump (VDJ) test is widely used for clinical assessment of ACL injury risk, but it is not clear whether such assessments are valid.

AIM: To examine if sports medicine professionals and coaches are able to identify players at risk of sustaining an ACL injury by visually assessing player performance during a VDJ test.

METHODS: 102 video clips of elite female handball and football players performing a baseline VDJ test were randomly extracted from a 738-person prospective cohort study that tracked ACL injuries. Of the sample, 20 of 102 went on to suffer an ACL injury. These …

Teaching Data Analysis Using Students' Own Data, Dmitry Kondrashov, Stefano Allesina

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

An Agent-Based Modeling Approach For Predicting The Behavior Of Bighead Carp (Hypophthalmichthys Nobilis) Under The Influence Of Acoustic Deterrence, Joey Gaudy, Craig Garzella

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Network Structure And Dynamics Of Biological Systems, Deena R. Schmidt

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Quantifying Distribution In Carbon Uptake Across A Global Measurement Network Of Terrestrial Ecosystems, John Zobitz, Madeline Oswood

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Integrating Mathematics And Biology In The Classroom: A Compendium Of Case Studies And Labs, Becky Sanft, Anne Walter

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Quantifying Pollen Traits To Build A Mathematical Model Of Pollen Competition - A Biologist's Perspective, Rob Swanson, Alex Capaldi

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Study On Discrete And Discrete Fractional Pharmacokinetics-Pharmacodynamics Models For Tumor Growth And Anti-Cancer Effects, Ferhan Atici, Ngoc Nguyen

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Classification Of Coronary Artery Disease In Non-Diabetic Patients Using Artificial Neural Networks, Demond Handley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Differences In Duration Of Untreated Psychosis For Racial And Ethnic Minority Groups With First-Episode Psychosis: An Updated Systematic Review And Meta-Analysis., Nicole Schoer, Chen Wei Huang, Kelly K. Anderson

Epidemiology and Biostatistics Publications

PURPOSE: Ethnic minority groups with early psychosis may have longer treatment delays, potentially leading to poorer outcomes. We updated a previous systematic review of the literature on racial and ethnic differences in duration of untreated psychosis (DUP) among people with first-episode psychosis.

RESULTS: Six of 17 studies described significant differences across aggregated racial groups; however, the pooled estimates did not show differences across groups. Additional data from this update allowed for disaggregated analyses, finding that Black-African groups have a shorter DUP, whereas Black-Caribbean groups have longer DUP, relative to White groups.

CONCLUSIONS: These findings highlight the importance of in-depth research …

Adaptive Feature Engineering Modeling For Ultrasound Image Classification For Decision Support, Hatwib Mugasa

Doctoral Dissertations

Ultrasonography is considered a relatively safe option for the diagnosis of benign and malignant cancer lesions due to the low-energy sound waves used. However, the visual interpretation of the ultrasound images is time-consuming and usually has high false alerts due to speckle noise. Improved methods of collection image-based data have been proposed to reduce noise in the images; however, this has proved not to solve the problem due to the complex nature of images and the exponential growth of biomedical datasets. Secondly, the target class in real-world biomedical datasets, that is the focus of interest of a biopsy, is usually …