Open Access. Powered by Scholars. Published by Universities.®
- Publication
- Publication Type
Articles 1 - 2 of 2
Full-Text Articles in Life Sciences
Strategic Plan For Genomic Competencies Into Undergraduate Nursing Curriculum, Myerann Royce M. Mangalino
Strategic Plan For Genomic Competencies Into Undergraduate Nursing Curriculum, Myerann Royce M. Mangalino
UNLV Theses, Dissertations, Professional Papers, and Capstones
Problem: As genomics research continues to grow in medicine and in popular culture, an educational gap in nursing is inevitable. Nurses must have a strong understanding of genetics and genomics to effectively integrate them into current practice.Objectives: The objective is to identify gaps in the current undergraduate curriculum and build threads that may be incorporated into the current curriculum to fill the identified gaps. Methods: The foundation of this project was the Essentials of Genetic and Genomic Nursing: Competencies, Curricula Guidelines, and Outcome Indicators, 2nd Edition (Consensus Panel on Genetic/Genomic Nursing Competencies, 2008). A strategic plan was created to increase …
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 …