| Title |
Improved Cancer Detection Using Artificial Intelligence: a Retrospective Evaluation of Missed Cancers on Mammography
|
|---|---|
| Published in |
Journal of Digital Imaging, April 2019
|
| DOI | 10.1007/s10278-019-00192-5 |
| Pubmed ID | |
| Authors |
Alyssa T. Watanabe, Vivian Lim, Hoanh X. Vu, Richard Chim, Eric Weise, Jenna Liu, William G. Bradley, Christopher E. Comstock |
X Demographics
The data shown below were collected from the profiles of 14 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 | 8 | 57% |
| Netherlands | 1 | 7% |
| India | 1 | 7% |
| Tanzania, United Republic of | 1 | 7% |
| Unknown | 3 | 21% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 64% |
| Practitioners (doctors, other healthcare professionals) | 4 | 29% |
| Scientists | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 174 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 19 | 11% |
| Student > Bachelor | 19 | 11% |
| Researcher | 16 | 9% |
| Student > Ph. D. Student | 12 | 7% |
| Unspecified | 9 | 5% |
| Other | 29 | 17% |
| Unknown | 70 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 34 | 20% |
| Computer Science | 19 | 11% |
| Nursing and Health Professions | 11 | 6% |
| Engineering | 7 | 4% |
| Unspecified | 6 | 3% |
| Other | 16 | 9% |
| Unknown | 81 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 26. 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 10 October 2020.
All research outputs
#1,460,225
of 25,391,471 outputs
Outputs from Journal of Digital Imaging
#19
of 1,125 outputs
Outputs of similar age
#32,001
of 357,723 outputs
Outputs of similar age from Journal of Digital Imaging
#2
of 34 outputs
Altmetric has tracked 25,391,471 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,125 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 98% 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 357,723 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 91% of its contemporaries.
We're also able to compare this research output to 34 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 97% of its contemporaries.