English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper reports on the assigning of MeSH (Medical Subject Headings) categories to Japanese terms in an English-Japanese dictionary using the titles and abstracts of articles indexed in MEDLINE. In a previous study, 30,000 of 80,000 terms in the dictionary were mapped to MeSH terms by normalized comparison. It was reasoned that if the remaining dictionary terms appeared in MEDLINE-indexed articles that are indexed using MeSH terms, then relevancies between the dictionary terms and MeSH terms could be calculated, and thus MeSH categories assigned. This study compares two approaches for calculating the weight matrix. One is the TF*IDF method and the other uses the inner product of two weight matrices. About 20,000 additional dictionary terms were identified in MEDLINE-indexed articles published between 2000 and 2004. The precision and recall of these algorithms were evaluated separately for MeSH terms and non-MeSH terms. Unfortunately, the precision and recall of the algorithms was not good, but this method will help with manual assignment of MeSH categories to dictionary terms.

Assigning categorical information to Japanese medical terms using MeSH and MEDLINE.