| Title |
Medical image semantic segmentation based on deep learning
|
|---|---|
| Published in |
Neural Computing and Applications, July 2017
|
| DOI | 10.1007/s00521-017-3158-6 |
| Authors |
Feng Jiang, Aleksei Grigorev, Seungmin Rho, Zhihong Tian, YunSheng Fu, Worku Jifara, Khan Adil, Shaohui Liu |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Rwanda | 1 | 25% |
| Chile | 1 | 25% |
| United States | 1 | 25% |
| Germany | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 102 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 21% |
| Student > Ph. D. Student | 16 | 16% |
| Researcher | 7 | 7% |
| Student > Bachelor | 6 | 6% |
| Lecturer | 4 | 4% |
| Other | 13 | 13% |
| Unknown | 35 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 32 | 31% |
| Engineering | 19 | 19% |
| Unspecified | 2 | 2% |
| Medicine and Dentistry | 2 | 2% |
| Agricultural and Biological Sciences | 2 | 2% |
| Other | 3 | 3% |
| Unknown | 42 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 16 November 2023.
All research outputs
#3,040,962
of 24,985,232 outputs
Outputs from Neural Computing and Applications
#34
of 2,493 outputs
Outputs of similar age
#53,227
of 317,750 outputs
Outputs of similar age from Neural Computing and Applications
#2
of 14 outputs
Altmetric has tracked 24,985,232 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,493 research outputs from this source. They receive a mean Attention Score of 1.4. This one has done particularly well, scoring higher than 98% 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 317,750 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.