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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms
|
|---|---|
| Published in |
BMC Bioinformatics, August 2018
|
| DOI | 10.1186/s12859-018-2277-0 |
| Pubmed ID | |
| Authors |
Hsin-Yi Tsao, Pei-Ying Chan, Emily Chia-Yu Su |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 206 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 206 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 24 | 12% |
| Student > Bachelor | 20 | 10% |
| Student > Master | 19 | 9% |
| Researcher | 16 | 8% |
| Student > Doctoral Student | 8 | 4% |
| Other | 27 | 13% |
| Unknown | 92 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 29 | 14% |
| Computer Science | 29 | 14% |
| Engineering | 19 | 9% |
| Nursing and Health Professions | 6 | 3% |
| Agricultural and Biological Sciences | 3 | 1% |
| Other | 20 | 10% |
| Unknown | 100 | 49% |
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 19 January 2020.
All research outputs
#14,462,984
of 23,173,635 outputs
Outputs from BMC Bioinformatics
#4,784
of 7,343 outputs
Outputs of similar age
#186,356
of 330,970 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 91 outputs
Altmetric has tracked 23,173,635 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 7,343 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 330,970 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.