Medical Document Clustering Using Ontology-Based Term Similarity Measures
Clicks: 43
ID: 278041
2010
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
12.6
/100
43 views
7 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #2 of 2 articles by views in Medical Informatics
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract is not available for this article.
Login to Search Abstract
| Reference Key |
zhang2010medicalmedical
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Zhang, Xiaodan;Jing, Liping;Hu, Xiaohua;Ng, Michael;Xia, Jiali;Zhou, Xiaohua; |
| Journal | Medical Informatics |
| Year | 2010 |
| DOI |
10.4018/978-1-60566-050-9.ch169
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.