Abstract
Healthcare and the treatment of illnesses are one of the most fundamental aspects of modern human life, and drugs are the easiest approach to healthcare. However, consuming drugs lead to diverse effects. We propose the use generic medicine names and it is important to note that while drugs with the same generic name serve similar purposes, they may also cause different side effects. This paper presents a strategy to address the issue of side effects by recommending alternative drugs that have the same therapeutic effect but with less detrimental effects. By integrating the generic names of drugs and data from social networks, more data can be obtained to arrive at meaningful conclusions. This paper proposes a new approach for analysing drug-induced side effects, with collecting, processing, and using data from social networks.
Original language | English |
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Pages (from-to) | 301-314 |
Number of pages | 14 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 18 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2017 |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (NRF-2015R1A2A1A05001845).
Publisher Copyright:
Copyright © 2017 Inderscience Enterprises Ltd.
All Science Journal Classification (ASJC) codes
- Information Systems
- Biochemistry, Genetics and Molecular Biology(all)
- Library and Information Sciences