↓ Skip to main content

Systems Medicine Disease: Disease Classification and Scalability Beyond Networks and Boundary Conditions

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, August 2018
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
10 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
52 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Systems Medicine Disease: Disease Classification and Scalability Beyond Networks and Boundary Conditions
Published in
Frontiers in Bioengineering and Biotechnology, August 2018
DOI 10.3389/fbioe.2018.00112
Pubmed ID
Authors

Richard Berlin, Russell Gruen, James Best

Abstract

In order to accommodate the forthcoming wealth of health and disease related information, from genome to body sensors to population and the environment, the approach to disease description and definition demands re-examination. Traditional classification methods remain trapped by history; to provide the descriptive features that are required for a comprehensive description of disease, systems science, which realizes dynamic processes, adaptive response, and asynchronous communication channels, must be applied (Wolkenhauer et al., 2013). When Disease is viewed beyond the thresholds of lines and threshold boundaries, disease definition is not only the result of reductionist, mechanistic categories which reluctantly face re-composition. Disease is process and synergy as the characteristics of Systems Biology and Systems Medicine are included. To capture the wealth of information and contribute meaningfully to medical practice and biology research, Disease classification goes beyond a single spatial biologic level or static time assignment to include the interface of Disease process and organism response (Bechtel, 2017a; Green et al., 2017).

Timeline

Login to access the full chart related to this output.

If you don’t have an account, click here to discover Explorer

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 17%
Student > Ph. D. Student 7 13%
Student > Master 6 12%
Student > Bachelor 3 6%
Lecturer 2 4%
Other 6 12%
Unknown 19 37%
Readers by discipline Count As %
Medicine and Dentistry 7 13%
Biochemistry, Genetics and Molecular Biology 7 13%
Computer Science 5 10%
Agricultural and Biological Sciences 3 6%
Immunology and Microbiology 3 6%
Other 5 10%
Unknown 22 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 26 December 2019.
All research outputs
#6,839,263
of 26,194,269 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#1,008
of 8,695 outputs
Outputs of similar age
#106,288
of 344,171 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#17
of 41 outputs
Altmetric has tracked 26,194,269 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 8,695 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done well, scoring higher than 88% 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 344,171 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 41 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 58% of its contemporaries.