A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).

ABSTRACT:

Background

Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs.

Principal findings

In the current study, the main work is to compare and analyze the p

SUBMITTER: Kuang Q 

PROVIDER: S-EPMC4152017 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature