| Title |
Differential Diagnosis Generators: an Evaluation of Currently Available Computer Programs
|
|---|---|
| Published in |
Journal of General Internal Medicine, July 2011
|
| DOI | 10.1007/s11606-011-1804-8 |
| Pubmed ID | |
| Authors |
William F. Bond, Linda M. Schwartz, Kevin R. Weaver, Donald Levick, Michael Giuliano, Mark L. Graber |
| Abstract |
Differential diagnosis (DDX) generators are computer programs that generate a DDX based on various clinical data. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 5% |
| Spain | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 131 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 16% |
| Student > Ph. D. Student | 20 | 14% |
| Student > Master | 14 | 10% |
| Student > Doctoral Student | 12 | 9% |
| Other | 11 | 8% |
| Other | 38 | 27% |
| Unknown | 22 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 54 | 39% |
| Computer Science | 17 | 12% |
| Agricultural and Biological Sciences | 8 | 6% |
| Nursing and Health Professions | 6 | 4% |
| Engineering | 6 | 4% |
| Other | 20 | 14% |
| Unknown | 29 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 August 2022.
All research outputs
#2,515,019
of 25,837,817 outputs
Outputs from Journal of General Internal Medicine
#1,834
of 8,256 outputs
Outputs of similar age
#11,970
of 133,811 outputs
Outputs of similar age from Journal of General Internal Medicine
#11
of 42 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,256 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.2. This one has done well, scoring higher than 77% 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 133,811 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 42 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 73% of its contemporaries.