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Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital…

Overview of attention for article published in BMC Medical Informatics and Decision Making, August 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
9 X users

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
140 Mendeley
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Title
Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors
Published in
BMC Medical Informatics and Decision Making, August 2021
DOI 10.1186/s12911-021-01603-w
Pubmed ID
Authors

Izidor Mlakar, Simon Lin, Ilona Aleksandraviča, Krista Arcimoviča, Jānis Eglītis, Mārcis Leja, Ángel Salgado Barreira, Jesús G. Gómez, Mercedes Salgado, Jesús G. Mata, Doroteja Batorek, Matej Horvat, Maja Molan, Maja Ravnik, Jean-François Kaux, Valérie Bleret, Catherine Loly, Didier Maquet, Elena Sartini, Urška Smrke

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 140 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 8%
Student > Master 9 6%
Unspecified 8 6%
Researcher 6 4%
Student > Doctoral Student 6 4%
Other 22 16%
Unknown 78 56%
Readers by discipline Count As %
Medicine and Dentistry 8 6%
Psychology 8 6%
Unspecified 8 6%
Nursing and Health Professions 6 4%
Computer Science 5 4%
Other 20 14%
Unknown 85 61%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 01 October 2021.
All research outputs
#6,695,536
of 23,881,329 outputs
Outputs from BMC Medical Informatics and Decision Making
#625
of 2,030 outputs
Outputs of similar age
#132,653
of 433,273 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 55 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,030 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 69% 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 433,273 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 69% of its contemporaries.
We're also able to compare this research output to 55 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 72% of its contemporaries.