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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Deep Learning in Medical Image Analysis
|
|---|---|
| Chapter number | 1 |
| Book title |
Deep Learning in Medical Image Analysis
|
| Published in |
Advances in experimental medicine and biology, February 2020
|
| DOI | 10.1007/978-3-030-33128-3_1 |
| Pubmed ID | |
| Book ISBNs |
978-3-03-033127-6, 978-3-03-033128-3
|
| Authors |
Heang-Ping Chan, Ravi K. Samala, Lubomir M. Hadjiiski, Chuan Zhou, Chan, Heang-Ping, Samala, Ravi K., Hadjiiski, Lubomir M., Zhou, Chuan |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 26% |
| Brazil | 1 | 4% |
| South Africa | 1 | 4% |
| Colombia | 1 | 4% |
| Spain | 1 | 4% |
| Italy | 1 | 4% |
| India | 1 | 4% |
| Netherlands | 1 | 4% |
| Algeria | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 9 | 39% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 17 | 74% |
| Science communicators (journalists, bloggers, editors) | 2 | 9% |
| Practitioners (doctors, other healthcare professionals) | 2 | 9% |
| Scientists | 2 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 1,093 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Pakistan | 1 | <1% |
| Australia | 1 | <1% |
| Unknown | 1090 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 161 | 15% |
| Student > Master | 141 | 13% |
| Researcher | 86 | 8% |
| Student > Bachelor | 81 | 7% |
| Student > Doctoral Student | 43 | 4% |
| Other | 134 | 12% |
| Unknown | 447 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 233 | 21% |
| Engineering | 163 | 15% |
| Medicine and Dentistry | 69 | 6% |
| Biochemistry, Genetics and Molecular Biology | 32 | 3% |
| Agricultural and Biological Sciences | 19 | 2% |
| Other | 107 | 10% |
| Unknown | 470 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 45. 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 06 March 2024.
All research outputs
#933,624
of 25,460,914 outputs
Outputs from Advances in experimental medicine and biology
#110
of 5,257 outputs
Outputs of similar age
#23,708
of 472,317 outputs
Outputs of similar age from Advances in experimental medicine and biology
#4
of 99 outputs
Altmetric has tracked 25,460,914 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,257 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done particularly well, scoring higher than 97% 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 472,317 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.