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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response
|
|---|---|
| Published in |
BioMedical Engineering OnLine, June 2021
|
| DOI | 10.1186/s12938-021-00899-z |
| Pubmed ID | |
| Authors |
Lal Hussain, Pauline Huang, Tony Nguyen, Kashif J. Lone, Amjad Ali, Muhammad Salman Khan, Haifang Li, Doug Young Suh, Tim Q. Duong |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 55 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 7% |
| Researcher | 4 | 7% |
| Student > Doctoral Student | 3 | 5% |
| Professor | 3 | 5% |
| Student > Ph. D. Student | 3 | 5% |
| Other | 4 | 7% |
| Unknown | 34 | 62% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 15% |
| Engineering | 8 | 15% |
| Medicine and Dentistry | 3 | 5% |
| Agricultural and Biological Sciences | 1 | 2% |
| Unknown | 35 | 64% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 16 August 2021.
All research outputs
#13,510,424
of 23,308,124 outputs
Outputs from BioMedical Engineering OnLine
#340
of 834 outputs
Outputs of similar age
#191,880
of 442,221 outputs
Outputs of similar age from BioMedical Engineering OnLine
#4
of 16 outputs
Altmetric has tracked 23,308,124 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 834 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 58% 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 442,221 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 55% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.