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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Decision support at home (DS@HOME) – system architectures and requirements
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, May 2012
|
| DOI | 10.1186/1472-6947-12-43 |
| Pubmed ID | |
| Authors |
Michael Marschollek |
| Abstract |
Demographic change with its consequences of an aging society and an increase in the demand for care in the home environment has triggered intensive research activities in sensor devices and smart home technologies. While many advanced technologies are already available, there is still a lack of decision support systems (DSS) for the interpretation of data generated in home environments. The aim of the research for this paper is to present the state-of-the-art in DSS for these data, to define characteristic properties of such systems, and to define the requirements for successful home care DSS implementations. |
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 % |
|---|---|---|
| India | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 136 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 17% |
| Student > Master | 23 | 17% |
| Researcher | 22 | 16% |
| Student > Doctoral Student | 11 | 8% |
| Student > Bachelor | 11 | 8% |
| Other | 24 | 17% |
| Unknown | 24 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 20% |
| Medicine and Dentistry | 19 | 14% |
| Engineering | 14 | 10% |
| Social Sciences | 11 | 8% |
| Nursing and Health Professions | 10 | 7% |
| Other | 28 | 20% |
| Unknown | 29 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 02 June 2012.
All research outputs
#15,245,883
of 22,668,244 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,305
of 1,978 outputs
Outputs of similar age
#104,790
of 165,043 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#34
of 44 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,978 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 24th percentile – i.e., 24% 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 165,043 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.