| Title |
An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study
|
|---|---|
| Published in |
The Lancet Digital Health, August 2020
|
| DOI | 10.1016/s2589-7500(20)30159-x |
| Pubmed ID | |
| Authors |
Liron Pantanowitz, Gabriela M Quiroga-Garza, Lilach Bien, Ronen Heled, Daphna Laifenfeld, Chaim Linhart, Judith Sandbank, Anat Albrecht Shach, Varda Shalev, Manuela Vecsler, Pamela Michelow, Scott Hazelhurst, Rajiv Dhir |
X Demographics
The data shown below were collected from the profiles of 58 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 | 11 | 19% |
| United Kingdom | 9 | 16% |
| France | 2 | 3% |
| Germany | 2 | 3% |
| Spain | 2 | 3% |
| India | 2 | 3% |
| Australia | 1 | 2% |
| Ecuador | 1 | 2% |
| Singapore | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 23 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 34 | 59% |
| Scientists | 14 | 24% |
| Practitioners (doctors, other healthcare professionals) | 8 | 14% |
| Science communicators (journalists, bloggers, editors) | 2 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 273 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 273 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 46 | 17% |
| Student > Ph. D. Student | 25 | 9% |
| Student > Master | 20 | 7% |
| Student > Bachelor | 20 | 7% |
| Other | 10 | 4% |
| Other | 40 | 15% |
| Unknown | 112 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 49 | 18% |
| Computer Science | 31 | 11% |
| Engineering | 17 | 6% |
| Biochemistry, Genetics and Molecular Biology | 16 | 6% |
| Agricultural and Biological Sciences | 8 | 3% |
| Other | 31 | 11% |
| Unknown | 121 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1056. 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 20 May 2024.
All research outputs
#15,305
of 25,992,468 outputs
Outputs from The Lancet Digital Health
#1
of 1 outputs
Outputs of similar age
#707
of 429,530 outputs
Outputs of similar age from The Lancet Digital Health
#1
of 1 outputs
Altmetric has tracked 25,992,468 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 1 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 1055.2. This one scored the same or higher as 0 of them.
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 429,530 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 99% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them