CB_1401 cY P06-20-02 Visualising Risk Factors for COVID-19: A Web-enabled Tool for Feature Engineering

Understanding risk factors of COVID-19 has quickly become a global demand to support decision making at an individual as well as national and international levels. Numerous hypotheses exist on sources of variability that lead to different levels of response and patient outcomes. Some of the widely reported sources of variability are obtained from early observed data (e.g. age, gender, etc.) While some are candidates for testing, such as immunization history, and treatment interventions. There remains a gap in our understanding of how these factors interact with each other and what their relative importance is when used as predictors of outcomes for specific patient cohorts. Web-enabled collaborative platforms are needed to empower stakeholders to test such hypothesis and share early findings quickly.