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Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2021
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Mentioned by

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1 X user

Citations

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26 Dimensions

Readers on

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132 Mendeley
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Title
Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks
Published in
BMC Medical Informatics and Decision Making, June 2021
DOI 10.1186/s12911-021-01553-3
Pubmed ID
Authors

Juan G. Diaz Ochoa, Orsolya Csiszár, Thomas Schimper

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 25 19%
Student > Ph. D. Student 12 9%
Student > Master 7 5%
Student > Bachelor 7 5%
Lecturer 6 5%
Other 17 13%
Unknown 58 44%
Readers by discipline Count As %
Unspecified 25 19%
Computer Science 10 8%
Engineering 9 7%
Business, Management and Accounting 8 6%
Medicine and Dentistry 7 5%
Other 13 10%
Unknown 60 45%
Attention Score in Context

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 25 August 2023.
All research outputs
#16,532,739
of 24,325,299 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,382
of 2,072 outputs
Outputs of similar age
#265,241
of 436,017 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#40
of 62 outputs
Altmetric has tracked 24,325,299 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,072 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. 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 436,017 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.