NORA Webinar: RENT – Repeated Elastic Net Technique for Feature Selection with Oliver Tomic (NMBU)
Feature selection is an important task in data analysis in general and especially with healthcare data where patients are often few, and features are many. Apart from prediction, interpretation of models is also of high importance and feature selection has a crucial role in this respect. By combining machine learning with component based multivariate statistical methods (chemometrics) one can design a workflow that helps medical staff gain deeper insights into their data.
In this webinar Oliver Tomic will show how RENT can help in finding stable biomarkers across subgroups of patients as well as giving a touch of personalised medicine by flagging patients that diverge from the rest.
Follow this link to register for the webinar:
About Oliver Tomic
Oliver is associated professor at the Institute of Data Science, Faculty of Science and Technology, Norwegian University of Life Science and member of CEHEADS (Centre for Healthcare Data Science, NMBU). Before starting in his position at NMBU in 2017, he was a senior research scientist at Nofima working with multivariate statistics applied to gas-sensor array data (electronic nose) and sensory and consumer data. He also was a senior researcher at the Norwegian Institute of Public Health (Folkehelseinstituttet) at the group for quality measurement of health services, measuring the performance of Norwegian hospitals using various quality indicators. His current research interests are analysis of healthcare data and life science data in general using multivariate statistics and machine learning.