Feature selection in detection of adverse drug reactions from the Health Improvement Network (THIN) database

Abstract

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 events, which are collected from day to day clinical practice. In this study we propose a novel concept of feature matrix to detect the ADRs. Feature matrix, which is extracted from high-throughput medical data from The Health Improvement Network (THIN) database, is created to characterize the medical events for the p..