| Title |
Figure Text Extraction in Biomedical Literature
|
|---|---|
| Published in |
PLOS ONE, January 2011
|
| DOI | 10.1371/journal.pone.0015338 |
| Pubmed ID | |
| Authors |
Daehyun Kim, Hong Yu |
| Abstract |
Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 4 | 6% |
| United States | 3 | 5% |
| United Kingdom | 2 | 3% |
| Portugal | 1 | 2% |
| Canada | 1 | 2% |
| Nigeria | 1 | 2% |
| France | 1 | 2% |
| Russia | 1 | 2% |
| Norway | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 47 | 73% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 20% |
| Student > Ph. D. Student | 12 | 19% |
| Student > Master | 9 | 14% |
| Professor | 5 | 8% |
| Other | 4 | 6% |
| Other | 15 | 23% |
| Unknown | 6 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 25 | 39% |
| Agricultural and Biological Sciences | 13 | 20% |
| Medicine and Dentistry | 7 | 11% |
| Engineering | 4 | 6% |
| Linguistics | 2 | 3% |
| Other | 8 | 13% |
| Unknown | 5 | 8% |