We will analyze healthcare data associated with COVID-tested individuals (including test results and clinical outcomes) to extract relationships between these data elements that correlate to development of a more severe disease state requiring timely and intensive medical intervention. The strengths of data feature relationships will be elucidated using machine-learning data science techniques to develop a clinical decision support alert system. This alert system will input patient data elements discovered during the research process and deemed relevant to disease severity prediction to compute a risk score for patients presenting to the clinic to help clinicians triage patients, interventions, and resources better.
