The data shown below were collected from the profiles of 48 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Time-Series Generative Adversarial Network Approach of Deep Learning Improves Seizure Detection From the Human Thalamic SEEG
|
|---|---|
| Published in |
Frontiers in Neurology, February 2022
|
| DOI | 10.3389/fneur.2022.755094 |
| Pubmed ID | |
| Authors |
Bhargava Ganti, Ganne Chaitanya, Ridhanya Sree Balamurugan, Nithin Nagaraj, Karthi Balasubramanian, Sandipan Pati |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 13% |
| India | 4 | 8% |
| Brazil | 2 | 4% |
| Canada | 1 | 2% |
| Germany | 1 | 2% |
| Ecuador | 1 | 2% |
| Sri Lanka | 1 | 2% |
| Kenya | 1 | 2% |
| Unknown | 31 | 65% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 44 | 92% |
| Scientists | 4 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 13% |
| Student > Master | 3 | 10% |
| Professor > Associate Professor | 2 | 6% |
| Researcher | 2 | 6% |
| Student > Bachelor | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 16 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 16% |
| Engineering | 3 | 10% |
| Neuroscience | 2 | 6% |
| Social Sciences | 1 | 3% |
| Unspecified | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 17 | 55% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 17 February 2024.
All research outputs
#1,611,819
of 25,927,633 outputs
Outputs from Frontiers in Neurology
#596
of 14,815 outputs
Outputs of similar age
#38,898
of 453,361 outputs
Outputs of similar age from Frontiers in Neurology
#23
of 826 outputs
Altmetric has tracked 25,927,633 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,815 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 95% 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 453,361 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 826 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.