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.
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.
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.
X Demographics
Attention Score in Context
| Title |
Towards an early warning system for monitoring of cancer patients using hybrid interactive machine learning
|
|---|---|
| Published in |
Frontiers in Digital Health, August 2024
|
| DOI | 10.3389/fdgth.2024.1443987 |
| Pubmed ID | |
| Authors |
Andreas Trojan, Emanuele Laurenzi, Stephan Jüngling, Sven Roth, Michael Kiessling, Ziad Atassi, Yannick Kadvany, Meinrad Mannhart, Christian Jackisch, Gerd Kullak-Ublick, Hans Friedrich Witschel |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
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 14 August 2024.
All research outputs
#23,772,997
of 26,462,556 outputs
Outputs from Frontiers in Digital Health
#899
of 910 outputs
Outputs of similar age
#103,505
of 133,833 outputs
Outputs of similar age from Frontiers in Digital Health
#10
of 19 outputs
Altmetric has tracked 26,462,556 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 910 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one is in the 1st percentile – i.e., 1% 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 133,833 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.