You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning Segmentation of Triple-Negative Breast Cancer (TNBC) Patient Derived Tumor Xenograft (PDX) and Sensitivity of Radiomic Pipeline to Tumor Probability Boundary
|
|---|---|
| Published in |
Cancers, July 2021
|
| DOI | 10.3390/cancers13153795 |
| Pubmed ID | |
| Authors |
Kaushik Dutta, Sudipta Roy, Timothy Daniel Whitehead, Jingqin Luo, Abhinav Kumar Jha, Shunqiang Li, James Dennis Quirk, Kooresh Isaac Shoghi |
X Demographics
The data shown below were collected from the profiles of 7 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 | 3 | 43% |
| Netherlands | 1 | 14% |
| Cuba | 1 | 14% |
| Unknown | 2 | 29% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 1 | 14% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 15% |
| Student > Ph. D. Student | 3 | 11% |
| Student > Bachelor | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Student > Master | 2 | 7% |
| Other | 4 | 15% |
| Unknown | 10 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 30% |
| Engineering | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Physics and Astronomy | 1 | 4% |
| Unknown | 14 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 26 January 2023.
All research outputs
#6,969,237
of 25,355,907 outputs
Outputs from Cancers
#3,217
of 15,412 outputs
Outputs of similar age
#131,550
of 428,217 outputs
Outputs of similar age from Cancers
#227
of 1,025 outputs
Altmetric has tracked 25,355,907 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 15,412 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 78% 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 428,217 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 1,025 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.