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Approved Research

Exploratory study to develop a machine learning predictive algorithm by characterizing and evaluating potential digital biomarkers of disease prognosis and severity in COVID-19 infected patients

Principal Investigator: Dr Sarah Kehoe
Approved Research ID: 69108
Approval date: January 25th 2021

Lay summary

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.