# Reports: error
Data Range: .

AERSMine: Goals

AERSMine enables focused {patients X meds} group comparisons and creates capability for carrying out high dimensional subset–based correlation analyses by virtue of finely segmented view of differential reporting patterns to identify demographics subgroups art highest risk of harmful interactions, and also facilitate to unravel latent relationships within large clinical effects data.

Schematic overview of the matrices

By partitioning the data matrices, AERSMine provides new insights on the inter-correlation between AEs and population subgroups to recognize potential safety signals that allow us to generate testable hypotheses based on risk-altering interactions.