Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
- Publication
- Publication Type
Articles 1 - 2 of 2
Full-Text Articles in Microarrays
Classification Of Coronary Artery Disease In Non-Diabetic Patients Using Artificial Neural Networks, Demond Handley
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.
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 …