| Title |
Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery
|
|---|---|
| Published in |
Journal of Clinical Monitoring and Computing, September 2018
|
| DOI | 10.1007/s10877-018-0200-x |
| Pubmed ID | |
| Authors |
Kamal Maheshwari, Jacek Cywinski, Piyush Mathur, Kenneth C. Cummings, Rafi Avitsian, Timothy Crone, David Liska, Francis X. Campion, Kurt Ruetzler, Andrea Kurz |
X Demographics
The data shown below were collected from the profiles of 3 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 | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 62 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 11 | 18% |
| Researcher | 8 | 13% |
| Unspecified | 4 | 6% |
| Other | 3 | 5% |
| Student > Doctoral Student | 3 | 5% |
| Other | 11 | 18% |
| Unknown | 22 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 26% |
| Unspecified | 4 | 6% |
| Business, Management and Accounting | 3 | 5% |
| Computer Science | 2 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 3% |
| Other | 9 | 15% |
| Unknown | 26 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 14 December 2018.
All research outputs
#13,275,341
of 23,108,064 outputs
Outputs from Journal of Clinical Monitoring and Computing
#338
of 704 outputs
Outputs of similar age
#164,581
of 340,834 outputs
Outputs of similar age from Journal of Clinical Monitoring and Computing
#4
of 10 outputs
Altmetric has tracked 23,108,064 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 704 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has gotten more attention than average, scoring higher than 51% 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 340,834 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.