A Partitioning-based Approach for Clustering COVID-19 Drugs and Co-Medication for Safe Use

Authors

  • Ahmad Alqurneh Universiti Tun Hussein Onn Malaysia
  • Aida Mustapha Universiti Tun Hussein Onn Malaysia
  • Nurfadhlina Mohd Sharef

Keywords:

COVID-19, Clustering, Partitioning, drugs

Abstract

Drugs Interaction (https://covid19-druginteractions.org/) is a website that allows users to select a COVID-19 drug among the nine popular drugs with one or more drug from a different class co-medication to check for any interaction between the chosen drugs. Beyond the interaction, however, the website does not advise if the resulting class of co-medication is safe to use or otherwise along with one of the nine COVID drugs. Therefore, there exist a need to use an unsupervised clustering approach to group the COVID drugs and respective co-medications that are safe to use in the absence of interaction and vice versa. This paper focused on application of the Partitioning Around Medoid (PAM) clustering algorithm to categorize the combinations as safe or otherwise. The resulting clusters are then measured using the Silhoutte value and presented.

Downloads

Download data is not yet available.

Downloads

Published

30-06-2020

How to Cite

Alqurneh, A., Mustapha, A., & Mohd Sharef, N. (2020). A Partitioning-based Approach for Clustering COVID-19 Drugs and Co-Medication for Safe Use . International Journal of Integrated Engineering, 12(5), 224–232. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/6334

Most read articles by the same author(s)