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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Sparse learning and stability selection for predicting MCI to AD conversion using baseline ADNI data
|
|---|---|
| Published in |
BMC Neurology, June 2012
|
| DOI | 10.1186/1471-2377-12-46 |
| Pubmed ID | |
| Authors |
Jieping Ye, Michael Farnum, Eric Yang, Rudi Verbeeck, Victor Lobanov, Nandini Raghavan, Gerald Novak, Allitia DiBernardo, Vaibhav A Narayan, for the Alzheimer’s Disease Neuroimaging Initiative |
| Abstract |
Patients with Mild Cognitive Impairment (MCI) are at high risk of progression to Alzheimer's dementia. Identifying MCI individuals with high likelihood of conversion to dementia and the associated biosignatures has recently received increasing attention in AD research. Different biosignatures for AD (neuroimaging, demographic, genetic and cognitive measures) may contain complementary information for diagnosis and prognosis of AD. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| Egypt | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 166 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Unknown | 165 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 30 | 18% |
| Student > Master | 26 | 16% |
| Researcher | 24 | 14% |
| Other | 10 | 6% |
| Student > Doctoral Student | 9 | 5% |
| Other | 30 | 18% |
| Unknown | 37 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 16% |
| Psychology | 22 | 13% |
| Medicine and Dentistry | 18 | 11% |
| Neuroscience | 14 | 8% |
| Engineering | 9 | 5% |
| Other | 25 | 15% |
| Unknown | 51 | 31% |
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 04 July 2012.
All research outputs
#13,867,609
of 22,669,724 outputs
Outputs from BMC Neurology
#1,169
of 2,415 outputs
Outputs of similar age
#94,831
of 164,520 outputs
Outputs of similar age from BMC Neurology
#24
of 43 outputs
Altmetric has tracked 22,669,724 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,415 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has gotten more attention than average, scoring higher than 50% 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 164,520 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.