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Case-based medical informatics

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2004
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)

Mentioned by

twitter
13 tweeters

Readers on

mendeley
118 Mendeley
citeulike
15 CiteULike
connotea
3 Connotea

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Summary Twitter Dimensions citations
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Title
Case-based medical informatics
Published in
BMC Medical Informatics and Decision Making, November 2004
DOI 10.1186/1472-6947-4-19
Pubmed ID
15533257
Authors

Stefan V Pantazi, José F Arocha, Jochen R Moehr

Abstract

The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine.

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Twitter Demographics

The data shown below were collected from the profiles of 13 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 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
United Kingdom 2 2%
Turkey 1 <1%
Indonesia 1 <1%
India 1 <1%
Taiwan 1 <1%
Canada 1 <1%
Unknown 109 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 17%
Student > Ph. D. Student 17 14%
Student > Master 16 14%
Other 12 10%
Professor 9 8%
Other 33 28%
Unknown 11 9%
Readers by discipline Count As %
Medicine and Dentistry 36 31%
Computer Science 30 25%
Social Sciences 10 8%
Agricultural and Biological Sciences 5 4%
Business, Management and Accounting 5 4%
Other 16 14%
Unknown 16 14%

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 09 September 2018.
All research outputs
#2,998,162
of 21,326,488 outputs
Outputs from BMC Medical Informatics and Decision Making
#271
of 1,859 outputs
Outputs of similar age
#15,746
of 113,879 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 21,326,488 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,859 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 85% 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 113,879 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 86% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them

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