Search

The aim of this paper is mining serendipitous drug usage to validate and generate drug repositioning hypotheses from social media. Materials and Methods: Two machine learning algorithms svm with sample size=12 and adaboost algorithm with sample size=12. Results: The support vector machine algorithm has shown more accuracy of (96. 66%) in reducing the false positive rates when compared with Adaboost algorithm accuracy(84.6%). The pre-test was calculated with a g-power value = 80% and threshold 0. 05% confidence interval of 95% mean and standard deviation by using the G-power tool. t is found that the svm algorithm has more accuracy percentage when compared with the Adaboost algorithm. [ABSTRACT FROM AUTHOR]