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X Demographics
Mendeley readers
Attention Score in Context
Title |
Scalable and accurate deep learning with electronic health records
|
---|---|
Published in |
npj Digital Medicine, May 2018
|
DOI | 10.1038/s41746-018-0029-1 |
Pubmed ID | |
Authors |
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg S. Corrado, Jeffrey Dean |
X Demographics
The data shown below were collected from the profiles of 2,031 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 | 648 | 32% |
United Kingdom | 134 | 7% |
Spain | 104 | 5% |
Canada | 60 | 3% |
France | 53 | 3% |
India | 45 | 2% |
Germany | 36 | 2% |
Australia | 27 | 1% |
Japan | 26 | 1% |
Other | 229 | 11% |
Unknown | 669 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1379 | 68% |
Scientists | 473 | 23% |
Practitioners (doctors, other healthcare professionals) | 146 | 7% |
Science communicators (journalists, bloggers, editors) | 32 | 2% |
Unknown | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 2,819 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2819 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 480 | 17% |
Researcher | 476 | 17% |
Student > Master | 310 | 11% |
Other | 179 | 6% |
Student > Bachelor | 165 | 6% |
Other | 470 | 17% |
Unknown | 739 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 702 | 25% |
Medicine and Dentistry | 390 | 14% |
Engineering | 202 | 7% |
Biochemistry, Genetics and Molecular Biology | 113 | 4% |
Agricultural and Biological Sciences | 98 | 3% |
Other | 440 | 16% |
Unknown | 874 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2022. 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 07 April 2024.
All research outputs
#4,595
of 25,765,370 outputs
Outputs from npj Digital Medicine
#1
of 1,030 outputs
Outputs of similar age
#67
of 342,375 outputs
Outputs of similar age from npj Digital Medicine
#1
of 17 outputs
Altmetric has tracked 25,765,370 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 1,030 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 57.9. This one has done particularly well, scoring higher than 99% 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 342,375 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 17 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.