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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, August 2020
|
| DOI | 10.3389/fncom.2020.00061 |
| Pubmed ID | |
| Authors |
Ujjwal Baid, Swapnil U. Rane, Sanjay Talbar, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Abhishek Mahajan |
X Demographics
The data shown below were collected from the profiles of 9 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 | 4 | 44% |
| Canada | 1 | 11% |
| Switzerland | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 78% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
| Scientists | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 88 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 11% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Student > Postgraduate | 4 | 5% |
| Other | 11 | 13% |
| Unknown | 43 | 49% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 11% |
| Computer Science | 7 | 8% |
| Engineering | 6 | 7% |
| Biochemistry, Genetics and Molecular Biology | 4 | 5% |
| Agricultural and Biological Sciences | 3 | 3% |
| Other | 13 | 15% |
| Unknown | 45 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 66. 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 29 June 2023.
All research outputs
#616,354
of 24,513,158 outputs
Outputs from Frontiers in Computational Neuroscience
#27
of 1,419 outputs
Outputs of similar age
#18,456
of 403,469 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#2
of 31 outputs
Altmetric has tracked 24,513,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,419 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done particularly well, scoring higher than 98% 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 403,469 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 95% of its contemporaries.
We're also able to compare this research output to 31 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 96% of its contemporaries.