COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity
Fig 5
LR coefficients obtained from the biochemistry data.
LR model provides direct access to the computed coefficients and summarizes information about the contribution of each feature in the final output. The positive or negative coefficient values indicate an increased or decreased weight passed to the logistic function, which results in obtaining a positive or negative answer, respectively. In our analysis of the disease progression, severe cases were labeled as positive. This allows the identification of the biochemical features related to case severity. To generate compatible coefficient values for parameters with different ranges (e.g. lymphocyte count typically ranges from 0 to 3 while CRP ranges from 0 to 200) we normalized the data using the l2 normalization.