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X Demographics
Mendeley readers
Attention Score in Context
Title |
Effective diagnosis of Alzheimer’s disease by means of large margin-based methodology
|
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Published in |
BMC Medical Informatics and Decision Making, July 2012
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DOI | 10.1186/1472-6947-12-79 |
Pubmed ID | |
Authors |
Rosa Chaves, Javier Ramírez, Juan M Górriz, Ignacio A Illán, Manuel Gómez-Río, Cristobal Carnero, the Alzheimer’s Disease Neuroimaging Initiative |
Abstract |
Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. |
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 % |
---|---|---|
United States | 1 | 50% |
India | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 3% |
United States | 1 | 3% |
Unknown | 38 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 30% |
Student > Ph. D. Student | 8 | 20% |
Student > Master | 5 | 13% |
Student > Postgraduate | 2 | 5% |
Student > Bachelor | 2 | 5% |
Other | 4 | 10% |
Unknown | 7 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 18% |
Computer Science | 7 | 18% |
Psychology | 4 | 10% |
Neuroscience | 3 | 8% |
Engineering | 3 | 8% |
Other | 5 | 13% |
Unknown | 11 | 28% |
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 05 August 2012.
All research outputs
#15,248,503
of 22,673,450 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,306
of 1,978 outputs
Outputs of similar age
#104,192
of 164,116 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#48
of 53 outputs
Altmetric has tracked 22,673,450 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 1,978 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 164,116 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 53 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.