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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy
|
|---|---|
| Published in |
Computers in Biology & Medicine, July 2021
|
| DOI | 10.1016/j.compbiomed.2021.104648 |
| Pubmed ID | |
| URN |
urn:issn:0010-4825
|
| Authors |
Tim Smole, Bojan Žunkovič, Matej Pičulin, Enja Kokalj, Marko Robnik-Šikonja, Matjaž Kukar, Dimitrios I Fotiadis, Vasileios C Pezoulas, Nikolaos S Tachos, Fausto Barlocco, Francesco Mazzarotto, Dejana Popović, Lars Maier, Lazar Velicki, Guy A MacGowan, Iacopo Olivotto, Nenad Filipović, Djordje G Jakovljević, Zoran Bosnić |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 20% |
| Italy | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 73 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 10% |
| Researcher | 6 | 8% |
| Student > Bachelor | 6 | 8% |
| Student > Master | 6 | 8% |
| Student > Doctoral Student | 5 | 7% |
| Other | 8 | 11% |
| Unknown | 35 | 48% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 10 | 14% |
| Medicine and Dentistry | 9 | 12% |
| Business, Management and Accounting | 3 | 4% |
| Mathematics | 2 | 3% |
| Nursing and Health Professions | 2 | 3% |
| Other | 8 | 11% |
| Unknown | 39 | 53% |
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 10 August 2022.
All research outputs
#14,559,962
of 25,411,814 outputs
Outputs from Computers in Biology & Medicine
#1,080
of 2,776 outputs
Outputs of similar age
#196,231
of 447,457 outputs
Outputs of similar age from Computers in Biology & Medicine
#66
of 156 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,776 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 60% 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 447,457 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 55% of its contemporaries.
We're also able to compare this research output to 156 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 56% of its contemporaries.