Detect adverse drug reactions for drug Pioglitazone

TL;DR

This paper introduces a new method for detecting adverse drug reactions (ADRs) by analyzing medical event data before and after drug intake, using feature selection to identify significant ADRs.

Contribution

The study presents a novel approach combining feature matrix construction and Student's t-test for ADR detection, demonstrating improved performance over existing methods.

Findings

Effective detection of ADRs for Pioglitazone

Outperforms other computerized ADR detection methods

Validates the use of feature selection in pharmacovigilance

Abstract

In this study we propose a novel method to successfully detect the ADRs using feature matrix and feature selection. A feature matrix, which characterizes the medical events before patients take drugs or after patients take drugs, is created from THIN database. The feature selection method of Student's t-test is used to detect the significant features from thousands of medical events. The significant ADRs, which are corresponding to significant features, are detected. Experiments are performed on the drug Pioglitazone. Compared to other computerized methods, our proposed method achieves good performance.