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Articles 1 - 14 of 14
Full-Text Articles in Biometry
Model For Calculating Impact Force For Individualized Hip Fracture Prediction During A Fall, Alisha Agarwal, Daniel Kargilis, Nishtha Gupta, Michael Chang, Rui Feng, Gregory Chang, Chamith S. Rajapakse
Model For Calculating Impact Force For Individualized Hip Fracture Prediction During A Fall, Alisha Agarwal, Daniel Kargilis, Nishtha Gupta, Michael Chang, Rui Feng, Gregory Chang, Chamith S. Rajapakse
Student Papers, Posters & Projects
Osteoporotic-related weakening of bone is a common cause of hip fractures. The standard of care for the diagnosis and management of osteoporosis is the dual-energy x-ray absorptiometry bone mineral density T-scores. Many individuals considered nonosteoporotic, however, still sustain fractures since these tools do not incorporate vital bone parameters and subject-specific characteristics. The purpose of this work was to (1) develop a simple analytical model for estimating the force exerted on the femur during a fall (i.e., impact force) based on measurable patient metrics and (2) define a quantifiable fracture risk index by comparing finite-element-derived bone strength and impact force, which …
Disparities In The Prevalence Of Hospitalizations And In-Hospital Mortality Due To Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study, Umar Hayat, Faisal Kamal, Muhammad Kamal, Wasique Mirza, Tariq Ahmad, Manesh Gangwani, Dushyant Dahiya, Hassam Ali, Shiva Naidoo, Sara Humayun, Hayrettin Okut, Muhammad Aziz
Disparities In The Prevalence Of Hospitalizations And In-Hospital Mortality Due To Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study, Umar Hayat, Faisal Kamal, Muhammad Kamal, Wasique Mirza, Tariq Ahmad, Manesh Gangwani, Dushyant Dahiya, Hassam Ali, Shiva Naidoo, Sara Humayun, Hayrettin Okut, Muhammad Aziz
Division of Gastroenterology and Hepatology Faculty Papers
Background: Non-alcoholic liver disease (NAFLD) may be associated with cardiovascular diseases; however, only a few studies have analyzed this relationship. We aimed to assess the epidemiologic data and the association between NAFLD and acute myocardial infarction (AMI) in the United States. Methods: The National Inpatient Sample (NIS) database 2016-2019 was queried using ICD10-CM diagnostic codes to identify hospitalizations of AMI + NAFLD. Essential demographic variables were analyzed to determine the disparities in the prevalence of AMI hospitalizations and deaths among NAFLD patients. Univariate and multivariate logistic regression models determined the association between NAFLD and AMI hospitalizations and death. …
Effects Of Sars-Cov-2 Variants On Cd8+ T Cell Epitope Diversity: Estimating Clinical Severity In The United States, Grace Kim, Jacob Elnaggar, Maya Sevalia, Najah Nicholas, Mallory Varnado, Judy Crabtree, Lucio Miele
Effects Of Sars-Cov-2 Variants On Cd8+ T Cell Epitope Diversity: Estimating Clinical Severity In The United States, Grace Kim, Jacob Elnaggar, Maya Sevalia, Najah Nicholas, Mallory Varnado, Judy Crabtree, Lucio Miele
School of Medicine Faculty Publications
Association for Clinical and Translational Science 2024; April 3 - April 5, 2024; Las Vegas, NV
Bisc 504: Biometry, Jason Hoeksema
Biological And Practical Implications Of Genome-Wide Association Study Of Schizophrenia Using Bayesian Variable Selection, Benazir Rowe, Xiangning Chen, Zuoheng Wang, Jingchun Chen, Amei Amei
Biological And Practical Implications Of Genome-Wide Association Study Of Schizophrenia Using Bayesian Variable Selection, Benazir Rowe, Xiangning Chen, Zuoheng Wang, Jingchun Chen, Amei Amei
School of Medicine Faculty Research
Genome-wide association studies (GWAS) have identified over 100 loci associated with schizophrenia. Most of these studies test genetic variants for association one at a time. In this study, we performed GWAS of the molecular genetics of schizophrenia (MGS) dataset with 5334 subjects using multivariate Bayesian variable selection (BVS) method Posterior Inference via Model Averaging and Subset Selection (piMASS) and compared our results with the previous univariate analysis of the MGS dataset. We showed that piMASS can improve the power of detecting schizophrenia-associated SNPs, potentially leading to new discoveries from existing data without increasing the sample size. We tested SNPs in …
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
Unified Methods For Feature Selection In Large-Scale Genomic Studies With Censored Survival Outcomes, Lauren Spirko-Burns, Karthik Devarajan
COBRA Preprint Series
One of the major goals in large-scale genomic studies is to identify genes with a prognostic impact on time-to-event outcomes which provide insight into the disease's process. With rapid developments in high-throughput genomic technologies in the past two decades, the scientific community is able to monitor the expression levels of tens of thousands of genes and proteins resulting in enormous data sets where the number of genomic features is far greater than the number of subjects. Methods based on univariate Cox regression are often used to select genomic features related to survival outcome; however, the Cox model assumes proportional hazards …
A Statistical Method For The Conservative Adjustment Of False Discovery Rate (Q-Value), Yinglei Lai
A Statistical Method For The Conservative Adjustment Of False Discovery Rate (Q-Value), Yinglei Lai
Epidemiology Faculty Publications
Background
q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation.
Results
We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p …
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
COBRA Preprint Series
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
UW Biostatistics Working Paper Series
We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the …
Mixtures Of Self-Modelling Regressions, Rhonda D. Szczesniak, Kert Viele, Robin L. Cooper
Mixtures Of Self-Modelling Regressions, Rhonda D. Szczesniak, Kert Viele, Robin L. Cooper
Statistics Faculty Publications
A shape invariant model for functions f1,...,fn specifies that each individual function fi can be related to a common shape function g through the relation fi(x) = aig(cix + di) + bi. We consider a flexible mixture model that allows multiple shape functions g1,...,gK, where each fi is a shape invariant transformation of one of those gK. We derive an MCMC algorithm for fitting the model using Bayesian Adaptive Regression Splines (BARS), propose …
Missing At Random And Ignorability For Inferences About Subsets Of Parameters With Missing Data, Roderick J. Little, Sahar Zanganeh
Missing At Random And Ignorability For Inferences About Subsets Of Parameters With Missing Data, Roderick J. Little, Sahar Zanganeh
The University of Michigan Department of Biostatistics Working Paper Series
For likelihood-based inferences from data with missing values, Rubin (1976) showed that the missing data mechanism can be ignored when (a) the missing data are missing at random (MAR), in the sense that missingness does not depend on the missing values after conditioning on the observed data, and (b) the parameters of the data model and the missing-data mechanism are distinct; that is, there are no a priori ties, via parameter space restrictions or prior distributions, between the parameters of the data model and the parameters of the model for the mechanism. Rubin described (a) and (b) as the "weakest …
Approximating Confidence Intervals About Discrete Time Survival/Cumulative Incidence Estimates Using The Delta Method, Alexis Dinno, Jong-Sung Kim
Approximating Confidence Intervals About Discrete Time Survival/Cumulative Incidence Estimates Using The Delta Method, Alexis Dinno, Jong-Sung Kim
Community Health Faculty Publications and Presentations
Poster focuses on answering the questions whether and when and event will happen in a population at risk.
Understanding The Physical Properties That Control Protein Crystallization By Analysis Of Largescale Experimental Data, W. Nicholson Price Ii, Yang Chen, Samuel K. Handelman, Helen Neely, Philip Manor, Richard Karlin, Rajesh Nair, Jinfeng Liu, Michael Baran, John Everett, Saichiu N. Tong, Farhad Forouhar, Swarup S. Swaminathan, Thomas Acton, Rong Xiao, Joseph R. Luft, Angela Lauricella, George T. Detitta, Burkhard Rost, Gaetano T. Montelione, John T. Hunt
Understanding The Physical Properties That Control Protein Crystallization By Analysis Of Largescale Experimental Data, W. Nicholson Price Ii, Yang Chen, Samuel K. Handelman, Helen Neely, Philip Manor, Richard Karlin, Rajesh Nair, Jinfeng Liu, Michael Baran, John Everett, Saichiu N. Tong, Farhad Forouhar, Swarup S. Swaminathan, Thomas Acton, Rong Xiao, Joseph R. Luft, Angela Lauricella, George T. Detitta, Burkhard Rost, Gaetano T. Montelione, John T. Hunt
Law Faculty Scholarship
Crystallization is the most serious bottleneck in high-throughput protein-structure determination by diffraction methods. We have used data mining of the large-scale experimental results of the Northeast Structural Genomics Consortium and experimental folding studies to characterize the biophysical properties that control protein crystallization. This analysis leads to the conclusion that crystallization propensity depends primarily on the prevalence of well-ordered surface epitopes capable of mediating interprotein interactions and is not strongly influenced by overall thermodynamic stability. We identify specific sequence features that correlate with crystallization propensity and that can be used to estimate the crystallization probability of a given construct. Analyses of …
Statistical Services, Jane Speijers, Australian Co-Operation With The National Agricultural Research Project, Thailand.
Statistical Services, Jane Speijers, Australian Co-Operation With The National Agricultural Research Project, Thailand.
All other publications
2. TERMS OF REFERENCE
To achieve familiarity with the existing resources for biometrical work within the Department of Agriculture both at Bangkhen and at the regional centres - and to gain an understanding of the present systems whereby biometricians are involved in designing experiments and analysing results. This will involve visits to research stations and discussions with both research directors and scientists.
2.1 To become informed on the planned improvements in biometrical services for regional research centres to be carried out through the Thai/World Bank, National Agricultural Research Project (NARP).
2.2 Against the background of items 2.1 and 2.2 above, …