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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automation of a problem list using natural language processing
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, August 2005
|
| DOI | 10.1186/1472-6947-5-30 |
| Pubmed ID | |
| Authors |
Stephane Meystre, Peter J Haug |
| Abstract |
The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However, the current problem list is usually incomplete and inaccurate, and is often totally unused. To alleviate this issue, we are building an environment where the problem list can be easily and effectively maintained. |
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 % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| Austria | 1 | <1% |
| United Kingdom | 1 | <1% |
| South Africa | 1 | <1% |
| Spain | 1 | <1% |
| Argentina | 1 | <1% |
| Unknown | 104 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 22% |
| Student > Master | 18 | 16% |
| Student > Ph. D. Student | 10 | 9% |
| Professor > Associate Professor | 10 | 9% |
| Student > Bachelor | 8 | 7% |
| Other | 27 | 24% |
| Unknown | 14 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 33 | 29% |
| Computer Science | 29 | 26% |
| Social Sciences | 5 | 4% |
| Agricultural and Biological Sciences | 4 | 4% |
| Engineering | 4 | 4% |
| Other | 19 | 17% |
| Unknown | 18 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 24 April 2019.
All research outputs
#3,109,136
of 22,736,112 outputs
Outputs from BMC Medical Informatics and Decision Making
#262
of 1,985 outputs
Outputs of similar age
#5,928
of 58,568 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 6 outputs
Altmetric has tracked 22,736,112 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,985 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done well, scoring higher than 86% 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 58,568 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 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.