The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Early Diagnosis of Hepatocellular Carcinoma Using Machine Learning Method
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, March 2020
|
| DOI | 10.3389/fbioe.2020.00254 |
| Pubmed ID | |
| Authors |
Zi-Mei Zhang, Jiu-Xin Tan, Fang Wang, Fu-Ying Dao, Zhao-Yue Zhang, Hao Lin |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 13% |
| Germany | 1 | 7% |
| Mexico | 1 | 7% |
| Venezuela, Bolivarian Republic of | 1 | 7% |
| Turkey | 1 | 7% |
| United Arab Emirates | 1 | 7% |
| Switzerland | 1 | 7% |
| Unknown | 7 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 12 | 80% |
| Scientists | 3 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 62 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 9 | 15% |
| Student > Master | 6 | 10% |
| Student > Ph. D. Student | 5 | 8% |
| Researcher | 4 | 6% |
| Lecturer | 1 | 2% |
| Other | 4 | 6% |
| Unknown | 33 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 8 | 13% |
| Computer Science | 5 | 8% |
| Medicine and Dentistry | 5 | 8% |
| Neuroscience | 2 | 3% |
| Social Sciences | 2 | 3% |
| Other | 5 | 8% |
| Unknown | 35 | 56% |
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 11 January 2022.
All research outputs
#4,271,858
of 23,394,089 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#607
of 7,009 outputs
Outputs of similar age
#92,628
of 369,393 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#52
of 367 outputs
Altmetric has tracked 23,394,089 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 7,009 research outputs from this source. They receive a mean Attention Score of 3.6. 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 369,393 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 74% of its contemporaries.
We're also able to compare this research output to 367 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.