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Incorporating medical code descriptions for diagnosis prediction in healthcare

Overview of attention for article published in BMC Medical Informatics and Decision Making, December 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
34 Mendeley
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Title
Incorporating medical code descriptions for diagnosis prediction in healthcare
Published in
BMC Medical Informatics and Decision Making, December 2019
DOI 10.1186/s12911-019-0961-2
Pubmed ID
Authors

Fenglong Ma, Yaqing Wang, Houping Xiao, Ye Yuan, Radha Chitta, Jing Zhou, Jing Gao

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Researcher 4 12%
Student > Master 3 9%
Student > Doctoral Student 2 6%
Other 2 6%
Other 3 9%
Unknown 14 41%
Readers by discipline Count As %
Computer Science 7 21%
Medicine and Dentistry 3 9%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Nursing and Health Professions 2 6%
Environmental Science 1 3%
Other 4 12%
Unknown 15 44%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 July 2021.
All research outputs
#6,488,820
of 20,034,281 outputs
Outputs from BMC Medical Informatics and Decision Making
#714
of 1,771 outputs
Outputs of similar age
#127,759
of 346,770 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#4
of 9 outputs
Altmetric has tracked 20,034,281 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,771 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 gotten more attention than average, scoring higher than 56% 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 346,770 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 62% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.