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EEG-based mild depression recognition using convolutional neural network

Overview of attention for article published in Medical & Biological Engineering & Computing, February 2019
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
10 Mendeley
Title
EEG-based mild depression recognition using convolutional neural network
Published in
Medical & Biological Engineering & Computing, February 2019
DOI 10.1007/s11517-019-01959-2
Pubmed ID
Authors

Xiaowei Li, Rong La, Ying Wang, Junhong Niu, Shuai Zeng, Shuting Sun, Jing Zhu

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 20%
Student > Bachelor 2 20%
Student > Doctoral Student 2 20%
Student > Ph. D. Student 2 20%
Student > Master 1 10%
Other 1 10%
Readers by discipline Count As %
Engineering 5 50%
Unspecified 2 20%
Computer Science 1 10%
Medicine and Dentistry 1 10%
Economics, Econometrics and Finance 1 10%
Other 0 0%

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 23 February 2019.
All research outputs
#11,537,379
of 12,980,854 outputs
Outputs from Medical & Biological Engineering & Computing
#1,271
of 1,349 outputs
Outputs of similar age
#210,679
of 248,390 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#7
of 10 outputs
Altmetric has tracked 12,980,854 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 1,349 research outputs from this source. They receive a mean Attention Score of 3.8. 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 248,390 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 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.