Anatomy Commons^™

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 …

Induction Of Differentiation Of Dental Pulp-Derived Mesenchymal Stem Cells (Dpsc), Aubrey Young

UNLV Theses, Dissertations, Professional Papers, and Capstones

Mesenchymal stem cells are derived from a variety of human tissues and are being bioengineered and studied for possible uses in the advancement of medicine. Recent efforts are being focused on Dental Pulp Stem Cells (DPSC's) due to the accessibility of this tissue. Many factors influence DPSC quality and quantity, including the specific methods used to isolate, collect, concentrate, and store these isolates once they are removed. Ancillary factors, such as the choice of media, the selection of early versus late passage cells, and cryopreservation techniques may also influence the differentiation potential and proliferative capacity of DPSC isolates.

The objective …