| Title |
A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery
|
|---|---|
| Published in |
Journal of Medical Systems, January 2019
|
| DOI | 10.1007/s10916-018-1151-y |
| Pubmed ID | |
| Authors |
Beiqun Zhao, Ruth S. Waterman, Richard D. Urman, Rodney A. Gabriel |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 119 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 15% |
| Researcher | 18 | 15% |
| Student > Master | 17 | 14% |
| Student > Bachelor | 11 | 9% |
| Student > Doctoral Student | 7 | 6% |
| Other | 16 | 13% |
| Unknown | 32 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 30 | 25% |
| Computer Science | 11 | 9% |
| Nursing and Health Professions | 10 | 8% |
| Engineering | 8 | 7% |
| Business, Management and Accounting | 4 | 3% |
| Other | 16 | 13% |
| Unknown | 40 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 15 January 2019.
All research outputs
#15,030,198
of 23,122,481 outputs
Outputs from Journal of Medical Systems
#639
of 1,166 outputs
Outputs of similar age
#250,319
of 435,934 outputs
Outputs of similar age from Journal of Medical Systems
#10
of 22 outputs
Altmetric has tracked 23,122,481 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,166 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 435,934 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.