| Title |
Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study
|
|---|---|
| Published in |
npj Digital Medicine, February 2021
|
| DOI | 10.1038/s41746-021-00398-4 |
| Pubmed ID | |
| Authors |
Endre Grøvik, Darvin Yi, Michael Iv, Elizabeth Tong, Line Brennhaug Nilsen, Anna Latysheva, Cathrine Saxhaug, Kari Dolven Jacobsen, Åslaug Helland, Kyrre Eeg Emblem, Daniel L. Rubin, Greg Zaharchuk |
X Demographics
The data shown below were collected from the profiles of 35 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 | 6 | 17% |
| Germany | 3 | 9% |
| Switzerland | 2 | 6% |
| Spain | 1 | 3% |
| Norway | 1 | 3% |
| Ireland | 1 | 3% |
| Netherlands | 1 | 3% |
| South Africa | 1 | 3% |
| Austria | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 16 | 46% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 20 | 57% |
| Scientists | 7 | 20% |
| Practitioners (doctors, other healthcare professionals) | 5 | 14% |
| Science communicators (journalists, bloggers, editors) | 3 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 50 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 16% |
| Student > Master | 8 | 16% |
| Student > Ph. D. Student | 5 | 10% |
| Student > Bachelor | 4 | 8% |
| Student > Doctoral Student | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 18 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 8 | 16% |
| Medicine and Dentistry | 6 | 12% |
| Engineering | 6 | 12% |
| Neuroscience | 2 | 4% |
| Physics and Astronomy | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 25 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 18 May 2021.
All research outputs
#1,879,160
of 24,522,750 outputs
Outputs from npj Digital Medicine
#446
of 878 outputs
Outputs of similar age
#49,892
of 424,590 outputs
Outputs of similar age from npj Digital Medicine
#34
of 61 outputs
Altmetric has tracked 24,522,750 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 878 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 54.4. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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 424,590 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 88% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.