| Title |
3D Printing, Computational Modeling, and Artificial Intelligence for Structural Heart Disease
|
|---|---|
| Published in |
JACC: Cardiovascular Imaging, August 2020
|
| DOI | 10.1016/j.jcmg.2019.12.022 |
| Pubmed ID | |
| Authors |
Dee Dee Wang, Zhen Qian, Marija Vukicevic, Sandy Engelhardt, Arash Kheradvar, Chuck Zhang, Stephen H Little, Johan Verjans, Dorin Comaniciu, William W O'Neill, Mani A Vannan |
X Demographics
The data shown below were collected from the profiles of 60 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 | 6 | 10% |
| Spain | 6 | 10% |
| India | 3 | 5% |
| Colombia | 3 | 5% |
| Germany | 2 | 3% |
| Ireland | 1 | 2% |
| Mexico | 1 | 2% |
| Chile | 1 | 2% |
| Guatemala | 1 | 2% |
| Other | 8 | 13% |
| Unknown | 28 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 45 | 75% |
| Scientists | 9 | 15% |
| Practitioners (doctors, other healthcare professionals) | 3 | 5% |
| Science communicators (journalists, bloggers, editors) | 3 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 199 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 26 | 13% |
| Student > Ph. D. Student | 20 | 10% |
| Student > Bachelor | 16 | 8% |
| Student > Master | 15 | 8% |
| Other | 11 | 6% |
| Other | 23 | 12% |
| Unknown | 88 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 37 | 19% |
| Engineering | 21 | 11% |
| Computer Science | 6 | 3% |
| Biochemistry, Genetics and Molecular Biology | 5 | 3% |
| Social Sciences | 4 | 2% |
| Other | 28 | 14% |
| Unknown | 98 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 32. 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 21 July 2022.
All research outputs
#1,231,551
of 25,387,668 outputs
Outputs from JACC: Cardiovascular Imaging
#396
of 2,700 outputs
Outputs of similar age
#34,542
of 424,952 outputs
Outputs of similar age from JACC: Cardiovascular Imaging
#16
of 114 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,700 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.1. This one has done well, scoring higher than 85% 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 424,952 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.