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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Deep Learning-Based Approach for Identifying the Medicinal Uses of Plant-Derived Natural Compounds
|
|---|---|
| Published in |
Frontiers in Pharmacology, November 2020
|
| DOI | 10.3389/fphar.2020.584875 |
| Pubmed ID | |
| Authors |
Sunyong Yoo, Hyung Chae Yang, Seongyeong Lee, Jaewook Shin, Seyoung Min, Eunjoo Lee, Minkeun Song, Doheon Lee |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 89 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 12% |
| Student > Bachelor | 10 | 11% |
| Student > Ph. D. Student | 8 | 9% |
| Student > Master | 5 | 6% |
| Student > Doctoral Student | 4 | 4% |
| Other | 13 | 15% |
| Unknown | 38 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 10% |
| Medicine and Dentistry | 9 | 10% |
| Agricultural and Biological Sciences | 6 | 7% |
| Computer Science | 4 | 4% |
| Chemistry | 4 | 4% |
| Other | 16 | 18% |
| Unknown | 41 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2023.
All research outputs
#6,115,999
of 24,567,524 outputs
Outputs from Frontiers in Pharmacology
#2,561
of 18,593 outputs
Outputs of similar age
#141,357
of 519,027 outputs
Outputs of similar age from Frontiers in Pharmacology
#101
of 490 outputs
Altmetric has tracked 24,567,524 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 18,593 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 519,027 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.