Drug Side Effect Analyser Using Machine Learning

Adarsh Bhat G, Abhilash Prajwal Dsouza, Rajgopal K.T, Jayadeva Bhat K, Mahesh Mahesh

Abstract


People are dependent on medicinal drugs on one way or the other for every simple cause such as headache, cold etc. Every drug has a negative impact on a person's body. Some people are unaware of the side effects of the drugs and they consume it without prescription. Social network platforms such as twitter provide an opportunity for people to express themselves. Using twitter as the source of data, this paper aims to find the side effects of drugs with the help of machine learning algorithms.SVM (Support Vector Machine) algorithm is used for drug related classification with an accuracy of 75%.Sentiment analysis is performed using VADER (Valence Aware Dictionary for sEntiment Reasoning) to handle negations, conjunctions and question marks present in the tweets. Keyword Extraction is performed using RAKE (Rapid Automatic Keyword Extraction) to get the side effects.


Keywords: -- Machine learning, Sentiment Analysis, Natural Language Processing, RAKE, SVM

Full Text:

PDF


DOI: https://doi.org/10.26483/ijarcs.v8i3.3109

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 International Journal of Advanced Research in Computer Science