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Mendeley readers
Attention Score in Context
| Title |
A random forest model based classification scheme for neonatal amplitude-integrated EEG
|
|---|---|
| Published in |
BioMedical Engineering OnLine, December 2014
|
| DOI | 10.1186/1475-925x-13-s2-s4 |
| Pubmed ID | |
| Authors |
Weiting Chen, Yu Wang, Guitao Cao, Guoqiang Chen, Qiufang Gu |
| Abstract |
Modern medical advances have greatly increased the survival rate of infants, while they remain in the higher risk group for neurological problems later in life. For the infants with encephalopathy or seizures, identification of the extent of brain injury is clinically challenging. Continuous amplitude-integrated electroencephalography (aEEG) monitoring offers a possibility to directly monitor the brain functional state of the newborns over hours, and has seen an increasing application in neonatal intensive care units (NICUs). |
Mendeley readers
The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 1% |
| Netherlands | 1 | 1% |
| Unknown | 81 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 13 | 16% |
| Researcher | 11 | 13% |
| Student > Bachelor | 10 | 12% |
| Student > Ph. D. Student | 7 | 8% |
| Student > Postgraduate | 4 | 5% |
| Other | 13 | 16% |
| Unknown | 25 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 18 | 22% |
| Engineering | 11 | 13% |
| Computer Science | 7 | 8% |
| Neuroscience | 5 | 6% |
| Psychology | 2 | 2% |
| Other | 8 | 10% |
| Unknown | 32 | 39% |
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 16 January 2015.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from BioMedical Engineering OnLine
#733
of 867 outputs
Outputs of similar age
#314,333
of 368,246 outputs
Outputs of similar age from BioMedical Engineering OnLine
#15
of 18 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 867 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 1st percentile – i.e., 1% 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 368,246 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 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.