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X Demographics
Mendeley readers
Attention Score in Context
Title |
A Novel Approach for Fully Automatic Intra-Tumor Segmentation With 3D U-Net Architecture for Gliomas
|
---|---|
Published in |
Frontiers in Computational Neuroscience, February 2020
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DOI | 10.3389/fncom.2020.00010 |
Pubmed ID | |
Authors |
Ujjwal Baid, Sanjay Talbar, Swapnil Rane, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Nilesh Sable, Mayuresh Akolkar, Abhishek Mahajan |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 5 | 50% |
France | 1 | 10% |
Canada | 1 | 10% |
Switzerland | 1 | 10% |
Unknown | 2 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 70% |
Scientists | 3 | 30% |
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 % |
---|---|---|
Unknown | 83 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 13% |
Researcher | 5 | 6% |
Student > Master | 5 | 6% |
Student > Bachelor | 5 | 6% |
Student > Doctoral Student | 4 | 5% |
Other | 16 | 19% |
Unknown | 37 | 45% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 16 | 19% |
Engineering | 14 | 17% |
Medicine and Dentistry | 5 | 6% |
Unspecified | 2 | 2% |
Neuroscience | 2 | 2% |
Other | 6 | 7% |
Unknown | 38 | 46% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 May 2020.
All research outputs
#5,834,774
of 23,195,584 outputs
Outputs from Frontiers in Computational Neuroscience
#273
of 1,364 outputs
Outputs of similar age
#107,759
of 360,513 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#14
of 36 outputs
Altmetric has tracked 23,195,584 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,364 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 79% 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 360,513 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.