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Biomedical Engineering and Bioengineering Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Biomedical Engineering and Bioengineering
Machine Learning Approaches For Fracture Risk Assessment: A Comparative Analysis Of Genomic And Phenotypic Data In 5130 Older Men, Qing Wu, Fatma Nasoz, Jongyun Jung, Bibek Bhattarai, Mira V. Han
Machine Learning Approaches For Fracture Risk Assessment: A Comparative Analysis Of Genomic And Phenotypic Data In 5130 Older Men, Qing Wu, Fatma Nasoz, Jongyun Jung, Bibek Bhattarai, Mira V. Han
Public Health Faculty Publications
The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Study (n = 5130), were analyzed. After a comprehensive genotype imputation, genetic risk score (GRS) was calculated from 1103 associated Single Nucleotide Polymorphisms for each participant. Data were normalized and split into a training set (80%) and a validation set (20%) for analysis. Random forest, gradient boosting, neural network, and logistic regression were used to develop prediction models for major osteoporotic fractures …
Resolving Intravoxel White Matter Structures In The Human Brain Using Regularized Regression And Clustering, Andrea Hart, Brianna Smith, Sean Smith, Elijah Sales, Jacqueline Hernandez-Camargo, Yarlin Mayor Garcia, Felix Zhan, Lori Griswold, Brian Dunkelberger, Michael R. Schwob, Sharang Chaudhry, Justin Zhan, Laxmi Gewali, Paul Oh
Resolving Intravoxel White Matter Structures In The Human Brain Using Regularized Regression And Clustering, Andrea Hart, Brianna Smith, Sean Smith, Elijah Sales, Jacqueline Hernandez-Camargo, Yarlin Mayor Garcia, Felix Zhan, Lori Griswold, Brian Dunkelberger, Michael R. Schwob, Sharang Chaudhry, Justin Zhan, Laxmi Gewali, Paul Oh
Computer Science Faculty Research
The human brain is a complex system of neural tissue that varies significantly between individuals. Although the technology that delineates these neural pathways does not currently exist, medical imaging modalities, such as diffusion magnetic resonance imaging (dMRI), can be leveraged for mathematical identification. The purpose of this work is to develop a novel method employing machine learning techniques to determine intravoxel nerve number and direction from dMRI data. The method was tested on multiple synthetic datasets and showed promising estimation accuracy and robustness for multi-nerve systems under a variety of conditions, including highly noisy data and imprecision in parameter assumptions.
Role Of Hydrodynamic Behavior Of Dna Molecules In Dielectrophoretic Polarization Under The Action Of An Electric Field, Hui Zhao
Mechanical Engineering Faculty Research
A continuum model is developed to predict the dielectrophoretic polarizability of coiled DNA molecules under the action of an alternating current electric field. The model approximates the coiled DNA molecule as a charged porous spherical particle. The model explains the discrepancies among scaling laws of polarizability of different-sized DNA molecules with contour length and such discrepancies are attributed to different hydrodynamic behavior. With zero or one fitting parameter, theoretical predictions are in good agreement with various experimental data, even though in experiments there are some uncertainties in regard to certain parameters.