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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis
|
|---|---|
| Published in |
Radiation Oncology, October 2018
|
| DOI | 10.1186/s13014-018-1140-9 |
| Pubmed ID | |
| Authors |
Wenzheng Sun, Mingyan Jiang, Jun Dang, Panchun Chang, Fang-Fang Yin |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Nigeria | 1 | 17% |
| United States | 1 | 17% |
| Spain | 1 | 17% |
| Netherlands | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 33% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 100 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 17% |
| Researcher | 13 | 13% |
| Student > Master | 8 | 8% |
| Student > Bachelor | 6 | 6% |
| Student > Postgraduate | 4 | 4% |
| Other | 16 | 16% |
| Unknown | 36 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 15% |
| Computer Science | 10 | 10% |
| Engineering | 10 | 10% |
| Biochemistry, Genetics and Molecular Biology | 6 | 6% |
| Physics and Astronomy | 5 | 5% |
| Other | 11 | 11% |
| Unknown | 43 | 43% |
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 03 January 2019.
All research outputs
#13,614,006
of 24,133,587 outputs
Outputs from Radiation Oncology
#535
of 2,073 outputs
Outputs of similar age
#162,435
of 348,399 outputs
Outputs of similar age from Radiation Oncology
#14
of 40 outputs
Altmetric has tracked 24,133,587 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,073 research outputs from this source. They receive a mean Attention Score of 2.9. This one has gotten more attention than average, scoring higher than 73% 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 348,399 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 52% of its contemporaries.
We're also able to compare this research output to 40 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 65% of its contemporaries.