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Ambient-aware continuous care through semantic context dissemination

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2014
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
51 Mendeley
Summary Twitter Dimensions citations
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Title
Ambient-aware continuous care through semantic context dissemination
Published in
BMC Medical Informatics and Decision Making, December 2014
DOI 10.1186/1472-6947-14-97
Pubmed ID
25476007
Authors

Femke Ongenae, Jeroen Famaey, Stijn Verstichel, Saar De Zutter, Steven Latré, Ann Ackaert, Piet Verhoeve, Filip De Turck

Abstract

The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e.g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate.The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data.

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Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 2%
Spain 1 2%
Unknown 49 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Student > Master 8 16%
Researcher 8 16%
Student > Doctoral Student 5 10%
Student > Bachelor 4 8%
Other 9 18%
Unknown 8 16%
Readers by discipline Count As %
Computer Science 15 29%
Social Sciences 5 10%
Engineering 4 8%
Nursing and Health Professions 2 4%
Medicine and Dentistry 2 4%
Other 10 20%
Unknown 13 25%

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 07 December 2014.
All research outputs
#15,311,799
of 22,772,779 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,309
of 1,984 outputs
Outputs of similar age
#213,581
of 360,775 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#26
of 36 outputs
Altmetric has tracked 22,772,779 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 1,984 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 360,775 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.

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