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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology
|
|---|---|
| Published in |
Radiation Oncology, April 2022
|
| DOI | 10.1186/s13014-022-02035-0 |
| Pubmed ID | |
| Authors |
Deepa Darshini Gunashekar, Lars Bielak, Leonard Hägele, Benedict Oerther, Matthias Benndorf, Anca-L. Grosu, Thomas Brox, Constantinos Zamboglou, Michael Bock |
X Demographics
The data shown below were collected from the profiles of 5 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 | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 62 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 16% |
| Student > Master | 9 | 15% |
| Researcher | 6 | 10% |
| Student > Bachelor | 2 | 3% |
| Lecturer | 1 | 2% |
| Other | 2 | 3% |
| Unknown | 32 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 10 | 16% |
| Computer Science | 6 | 10% |
| Medicine and Dentistry | 4 | 6% |
| Nursing and Health Professions | 2 | 3% |
| Business, Management and Accounting | 1 | 2% |
| Other | 4 | 6% |
| Unknown | 35 | 56% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 14 July 2023.
All research outputs
#3,909,803
of 24,076,951 outputs
Outputs from Radiation Oncology
#114
of 2,071 outputs
Outputs of similar age
#83,523
of 430,636 outputs
Outputs of similar age from Radiation Oncology
#3
of 37 outputs
Altmetric has tracked 24,076,951 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,071 research outputs from this source. They receive a mean Attention Score of 2.9. 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 430,636 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 80% of its contemporaries.
We're also able to compare this research output to 37 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 94% of its contemporaries.