About | Contact Us | Register | Login
ProceedingsSeriesJournalsSearchEAI
mca 22(2): e5

Research Article

The similarity between Disease and Drug Network in Link Prediction

Download466 downloads
Cite
BibTeX Plain Text
  • @ARTICLE{10.4108/eetmca.v7i2.2667,
        author={Muhammad Azam and Muhammad Nouman},
        title={The similarity between Disease and Drug Network in Link Prediction},
        journal={EAI Endorsed Transactions on Mobile Communications and Applications},
        volume={7},
        number={2},
        publisher={EAI},
        journal_a={MCA},
        year={2022},
        month={9},
        keywords={Social Network Analysis, Link Prediction, Disease, Drug networks},
        doi={10.4108/eetmca.v7i2.2667}
    }
    
  • Muhammad Azam
    Muhammad Nouman
    Year: 2022
    The similarity between Disease and Drug Network in Link Prediction
    MCA
    EAI
    DOI: 10.4108/eetmca.v7i2.2667
Muhammad Azam1,*, Muhammad Nouman2
  • 1: University of Missouri
  • 2: University of Agriculture Faisalabad
*Contact email: Writetoazamkhalid@gmail.com

Abstract

Nowadays, data records are being transferred entirely to digital platforms, and data have become embodied and measurable. In this study, to observe the relationship between disease and drug, we first constructed disease and drug networks. These networks consist of a disease diagnosis and drugs written by doctors. After the disease and drug networks were generated, a link prediction was done concerning similarity values between nodes. Experimental results show that the proposed method finds satisfactory results. By examining these constructions and connections it is feasible to achieve affinities, similitudes, and patterns and it is likewise conceivable to make it feasible to achieve.

Keywords
Social Network Analysis, Link Prediction, Disease, Drug networks
Received
2022-05-06
Accepted
2022-08-27
Published
2022-09-05
Publisher
EAI
http://dx.doi.org/10.4108/eetmca.v7i2.2667

Copyright © 2022 Muhammad Azam et al., licensed to EAI. This is an open access article distributed under the terms of the CC BYNC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

EBSCOProQuestDBLPDOAJPortico
EAI Logo

About EAI

  • Who We Are
  • Leadership
  • Research Areas
  • Partners
  • Media Center

Community

  • Membership
  • Conference
  • Recognition
  • Sponsor Us

Publish with EAI

  • Publishing
  • Journals
  • Proceedings
  • Books
  • EUDL