Detect Adverse Drug Reactions for Drug Aspirin

TL;DR

This paper introduces a novel feature matrix and selection approach to detect adverse drug reactions for Aspirin, achieving improved performance over existing methods, though further validation is required.

Contribution

The study presents an original method combining feature matrix and selection for ADR detection, enhancing accuracy over previous computerized techniques.

Findings

Major side effects of Aspirin identified

Improved detection performance achieved

Further investigation needed for validation

Abstract

Adverse drug reaction (ADR) is widely concerned for public health issue. 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 Aspirin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. The detected ADRs are based on the computerized method, further investigation is needed.