This paper is in the following e-collection/theme issue:

Ontologies, Classifications, and Coding (243) Natural Language Processing (706)

Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29667, first published .
A Word Pair Dataset for Semantic Similarity and Relatedness in Korean Medical Vocabulary: Reference Development and Validation

A Word Pair Dataset for Semantic Similarity and Relatedness in Korean Medical Vocabulary: Reference Development and Validation

A Word Pair Dataset for Semantic Similarity and Relatedness in Korean Medical Vocabulary: Reference Development and Validation

Authors of this article:

Yunjin Yum1, 2 Author Orcid Image ;   Jeong Moon Lee2 Author Orcid Image ;   Moon Joung Jang2 Author Orcid Image ;   Yoojoong Kim2 Author Orcid Image ;   Jong-Ho Kim2, 3 Author Orcid Image ;   Seongtae Kim4 Author Orcid Image ;   Unsub Shin4 Author Orcid Image ;   Sanghoun Song4 Author Orcid Image ;   Hyung Joon Joo3, 5, 6 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Kim Y, Kim J, Lee J, Jang M, Yum Y, Kim S, Shin U, Kim Y, Joo H, Song S. A pre-trained BERT for Korean medical natural language processing. Scientific Reports 2022;12(1) View
  2. Melton C, White B, Davis R, Bednarczyk R, Shaban-Nejad A. Fine-tuned Sentiment Analysis of COVID-19 Vaccine–Related Social Media Data: Comparative Study. Journal of Medical Internet Research 2022;24(10):e40408 View