Detection and Classification of Adverse Drug Reaction Using Opinion Mining and Artificial Neural Network Techniques: A Review

  • M. Janaki, Dr. S. N. Geethalakshmi

Abstract

Wide clinical trials are necessary before a drug accommodates in the trade place. Even so, it is crucial to analyze the later reactions of Adverse Drug Reactions (ADR) for any authorized drugs. ADRs are the later reactions that happens when picking the drug in an inborn way, which is a communal wellness affair, as millions of convalescent are taking various kinds of drug globally. They preliminary analyses of ADRs declines the expensesin a profitable way and evades mortality. The common web based networks like twitter can afford with passive users generated content that furnish the judgment of persons on various disciplines. So, the accessibility of the large datasets provides huge number of investigation for analyzing ADRs of any drugs. Opinion mining is the algorithmic way of analyzing the human idea for any object. In recent years, Sentiment Analysis (SA) and Machine Learning (ML) ideas have been taken into consideration in the area of data science for ADR observation. Significant provocations in this area are classified into three important kinds such as data pre-processing, extracting meaningful features from twitter data, and choosing the finest modal for classification. The keyobjective of this paper is to analyze the present condition of the research work in their discipline on SA and ML methods.

Published
2021-11-23
How to Cite
M. Janaki, Dr. S. N. Geethalakshmi. (2021). Detection and Classification of Adverse Drug Reaction Using Opinion Mining and Artificial Neural Network Techniques: A Review. Design Engineering, 15509-15521. Retrieved from http://www.thedesignengineering.com/index.php/DE/article/view/6686
Section
Articles