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Mendeley readers
Attention Score in Context
| Title |
The neurological disease ontology
|
|---|---|
| Published in |
Journal of Biomedical Semantics, December 2013
|
| DOI | 10.1186/2041-1480-4-42 |
| Pubmed ID | |
| Authors |
Mark Jensen, Alexander P Cox, Naveed Chaudhry, Marcus Ng, Donat Sule, William Duncan, Patrick Ray, Bianca Weinstock-Guttman, Barry Smith, Alan Ruttenberg, Kinga Szigeti, Alexander D Diehl |
| Abstract |
We are developing the Neurological Disease Ontology (ND) to provide a framework to enable representation of aspects of neurological diseases that are relevant to their treatment and study. ND is a representational tool that addresses the need for unambiguous annotation, storage, and retrieval of data associated with the treatment and study of neurological diseases. ND is being developed in compliance with the Open Biomedical Ontology Foundry principles and builds upon the paradigm established by the Ontology for General Medical Science (OGMS) for the representation of entities in the domain of disease and medical practice. Initial applications of ND will include the annotation and analysis of large data sets and patient records for Alzheimer's disease, multiple sclerosis, and stroke. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
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 % |
|---|---|---|
| United States | 3 | 4% |
| United Kingdom | 2 | 3% |
| Mexico | 1 | 1% |
| Unknown | 64 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 23% |
| Student > Ph. D. Student | 11 | 16% |
| Student > Bachelor | 8 | 11% |
| Professor | 6 | 9% |
| Professor > Associate Professor | 6 | 9% |
| Other | 11 | 16% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 17% |
| Agricultural and Biological Sciences | 10 | 14% |
| Medicine and Dentistry | 7 | 10% |
| Engineering | 5 | 7% |
| Chemistry | 4 | 6% |
| Other | 16 | 23% |
| Unknown | 16 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 24 December 2013.
All research outputs
#16,066,912
of 23,847,962 outputs
Outputs from Journal of Biomedical Semantics
#233
of 358 outputs
Outputs of similar age
#197,943
of 312,120 outputs
Outputs of similar age from Journal of Biomedical Semantics
#25
of 28 outputs
Altmetric has tracked 23,847,962 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 358 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 20th percentile – i.e., 20% 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 312,120 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.