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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep learning assessment of left ventricular hypertrophy based on electrocardiogram
|
|---|---|
| Published in |
Frontiers in Cardiovascular Medicine, August 2022
|
| DOI | 10.3389/fcvm.2022.952089 |
| Pubmed ID | |
| Authors |
Xiaoli Zhao, Guifang Huang, Lin Wu, Min Wang, Xuemin He, Jyun-Rong Wang, Bin Zhou, Yong Liu, Yesheng Lin, Dinghui Liu, Xianguan Yu, Suzhen Liang, Borui Tian, Linxiao Liu, Yanming Chen, Shuhong Qiu, Xujing Xie, Lanqing Han, Xiaoxian Qian |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 15% |
| Student > Master | 2 | 15% |
| Student > Ph. D. Student | 2 | 15% |
| Unspecified | 1 | 8% |
| Researcher | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 31% |
| Engineering | 3 | 23% |
| Business, Management and Accounting | 1 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Unknown | 4 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 24 November 2023.
All research outputs
#4,582,991
of 24,862,965 outputs
Outputs from Frontiers in Cardiovascular Medicine
#707
of 8,761 outputs
Outputs of similar age
#90,826
of 423,689 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#78
of 992 outputs
Altmetric has tracked 24,862,965 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,761 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 91% 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 423,689 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 992 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.