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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Intelligent diagnosis with Chinese electronic medical records based on convolutional neural networks
|
|---|---|
| Published in |
BMC Bioinformatics, February 2019
|
| DOI | 10.1186/s12859-019-2617-8 |
| Pubmed ID | |
| Authors |
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du, Jian Chen, Jinzhun Wu |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| France | 1 | 20% |
| Germany | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 70 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 17% |
| Student > Ph. D. Student | 8 | 11% |
| Student > Master | 8 | 11% |
| Student > Doctoral Student | 4 | 6% |
| Student > Bachelor | 4 | 6% |
| Other | 11 | 16% |
| Unknown | 23 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 21% |
| Medicine and Dentistry | 7 | 10% |
| Nursing and Health Professions | 3 | 4% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Linguistics | 2 | 3% |
| Other | 12 | 17% |
| Unknown | 28 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 08 February 2019.
All research outputs
#14,437,494
of 23,125,690 outputs
Outputs from BMC Bioinformatics
#4,776
of 7,334 outputs
Outputs of similar age
#237,357
of 438,256 outputs
Outputs of similar age from BMC Bioinformatics
#118
of 199 outputs
Altmetric has tracked 23,125,690 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,334 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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 438,256 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.