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X Demographics
Mendeley readers
Attention Score in Context
Title |
MT-nCov-Net: A Multitask Deep-Learning Framework for Efficient Diagnosis of COVID-19 Using Tomography Scans
|
---|---|
Published in |
IEEE Transactions on Cybernetics, January 2023
|
DOI | 10.1109/tcyb.2021.3123173 |
Pubmed ID | |
Authors |
Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, Osama M. ELkomy |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 16 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Lecturer | 2 | 13% |
Student > Master | 1 | 6% |
Unspecified | 1 | 6% |
Student > Doctoral Student | 1 | 6% |
Professor | 1 | 6% |
Other | 2 | 13% |
Unknown | 8 | 50% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 3 | 19% |
Unspecified | 1 | 6% |
Psychology | 1 | 6% |
Economics, Econometrics and Finance | 1 | 6% |
Energy | 1 | 6% |
Other | 1 | 6% |
Unknown | 8 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 09 November 2021.
All research outputs
#5,343,131
of 25,392,582 outputs
Outputs from IEEE Transactions on Cybernetics
#87
of 1,478 outputs
Outputs of similar age
#110,409
of 474,963 outputs
Outputs of similar age from IEEE Transactions on Cybernetics
#2
of 120 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,478 research outputs from this source. They receive a mean Attention Score of 2.5. This one has done particularly well, scoring higher than 94% 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 474,963 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 120 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 98% of its contemporaries.