  Adverse drug reaction (ADR) is widely concerned for public health issue. ADRs
are one of most common causes to withdraw some drugs from market. Prescription
event monitoring (PEM) is an important approach to detect the adverse drug
reactions. The main problem to deal with this method is how to automatically
extract the medical events or side effects from high-throughput medical data,
which are collected from day to day clinical practice. In this study we propose
an original approach to detect the ADRs using feature matrix and feature
selection. The experiments are carried out on the drug Pravastatin. Major side
effects for the drug are detected. The detected ADRs are based on computerized
method, further investigation is needed.
