Mining Online Drug Reviews Database for the Treatment of Rheumatoid Arthritis by using Deep Learning


Pinar Yildirim, Istanbul Okan University, Turkey


In this paper, a research study for online patient reviews is introduced. Rheumatoid arthritis is a long-term and disabling autoimmune disease. Today, a huge amount of people have rheumatoid arthritis in the world. Considering the importance of the medication of rheumatoid arthritis, we aimed to investigate patient reviews in WebMD database and get some useful information for this disease. Our results revealed that etanercept treatment has the highest number of reviews. Data analysis was applied to discover knowledge on this drug. Deep learning approach was used to predict the effectiveness of etanercept and classification results were compared with other traditional classifiers. According to the comparison of classifiers, deep neural network has better accuracy metrics than others. Therefore, the results highlight that deep learning can be encouraging for medical data analyses. We hope that our study can make contributions to intelligent data analysis in medical domain.


Classification, Deep Learning, Etanercept, Online Drug Reviews.

Full Text  Volume 12, Number 15