| Title |
Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning
|
|---|---|
| Published in |
Nature Biotechnology, November 2021
|
| DOI | 10.1038/s41587-021-01094-0 |
| Pubmed ID | |
| Authors |
Noah F. Greenwald, Geneva Miller, Erick Moen, Alex Kong, Adam Kagel, Thomas Dougherty, Christine Camacho Fullaway, Brianna J. McIntosh, Ke Xuan Leow, Morgan Sarah Schwartz, Cole Pavelchek, Sunny Cui, Isabella Camplisson, Omer Bar-Tal, Jaiveer Singh, Mara Fong, Gautam Chaudhry, Zion Abraham, Jackson Moseley, Shiri Warshawsky, Erin Soon, Shirley Greenbaum, Tyler Risom, Travis Hollmann, Sean C. Bendall, Leeat Keren, William Graf, Michael Angelo, David Van Valen |
X Demographics
The data shown below were collected from the profiles of 296 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 | 93 | 31% |
| Germany | 14 | 5% |
| United Kingdom | 12 | 4% |
| France | 7 | 2% |
| Australia | 7 | 2% |
| India | 5 | 2% |
| Italy | 4 | 1% |
| Switzerland | 4 | 1% |
| Canada | 4 | 1% |
| Other | 38 | 13% |
| Unknown | 108 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 161 | 54% |
| Scientists | 124 | 42% |
| Practitioners (doctors, other healthcare professionals) | 9 | 3% |
| Science communicators (journalists, bloggers, editors) | 2 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 474 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 474 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 82 | 17% |
| Researcher | 82 | 17% |
| Student > Master | 35 | 7% |
| Student > Bachelor | 25 | 5% |
| Other | 15 | 3% |
| Other | 55 | 12% |
| Unknown | 180 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 84 | 18% |
| Computer Science | 45 | 9% |
| Agricultural and Biological Sciences | 40 | 8% |
| Engineering | 22 | 5% |
| Immunology and Microbiology | 21 | 4% |
| Other | 68 | 14% |
| Unknown | 194 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 181. 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 30 March 2024.
All research outputs
#226,570
of 25,815,269 outputs
Outputs from Nature Biotechnology
#467
of 8,627 outputs
Outputs of similar age
#6,191
of 519,842 outputs
Outputs of similar age from Nature Biotechnology
#12
of 106 outputs
Altmetric has tracked 25,815,269 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,627 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.5. 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 519,842 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 106 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.