Ngo, Duc Luu and Yamato, Naoki and Tran, Vu Anh and Nguyen, Ngoc Giang and Phan, Dau and Lumbanraja, Favorisen R and Kubo, Mamoru and Satou, Kenji Application of Word Embedding to Drug Repositioning. Journal Biomedical Science and Engineering, 9 (1). pp. 7-16. ISSN 1937-688X


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As a key technology of rapid and low-cost drug development, drug repositioning is getting popular. In this study, a text mining approach to the discovery of unknown drug-disease relation was tested. Using a word embedding algorithm, senses of over 1.7 million words were well represented in sufficiently short feature vectors. Through various analysis including clustering and classification, feasibility of our approach was tested. Finally, our trained classification model achieved 87.6% accuracy in the prediction of drug-disease relation in cancer treatment and succeeded in discovering novel drug-disease relations that were actually reported in recent studies.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA) > Prodi Ilmu Komputer
Depositing User: Favorisen R Lumbanraja
Date Deposited: 24 Feb 2021 05:04
Last Modified: 24 Feb 2021 05:04

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