t-SNE Visualization of Vector Pairs of Similar and Dissimilar Definition Sentences Created by Word2vec and Doc2vec in Japanese Medical Device Adverse Event Terminology

Ayako Yagahara; Masahito Uesugi; Hideto Yokoi

doi:10.3233/SHTI220266

t-SNE Visualization of Vector Pairs of Similar and Dissimilar Definition Sentences Created by Word2vec and Doc2vec in Japanese Medical Device Adverse Event Terminology

Stud Health Technol Inform. 2022 Jun 6:290:1058-1059. doi: 10.3233/SHTI220266.

Authors

Ayako Yagahara^{1

2}, Masahito Uesugi³, Hideto Yokoi⁴

Affiliations

¹ Department of Radiological Technology, Hokkaido University of Science, Sapporo, Hokkaido, Japan.
² Faculty of Health Sciences, Hokkaido University, Sapporo, Hokkaido, Japan.
³ Department of Medical Management and Informatics, Hokkaido Information University, Sapporo, Hokkaido, Japan.
⁴ Department of Medical Informatics, Kagawa University Hospital, kita-gun, Kagawa, Japan.

PMID: 35673204
DOI: 10.3233/SHTI220266

Abstract

The purpose of our study is to identify the patterns of vectors in similar/dissimilar pairs of definition sentence created by Word2vec and doec2vec for elaboration of the terminology for Japanese Medical Device Adverse Events. 2-dimension vector space created by t-SNE showed that the pair with true positive located closer in a vector space, especially Doc2vec had a strong tendency. Comparing with Word2vec, Similar vectors in Doc2vec were close and tended to form clusters.

Keywords: Equipment and Supplies; Machine learning; Terminology.

MeSH terms

Japan
Language*