| Title |
A Nomogram Based on CT Deep Learning Signature: A Potential Tool for the Prediction of Overall Survival in Resected Non-Small Cell Lung Cancer Patients
|
|---|---|
| Published in |
Cancer Management and Research, March 2021
|
| DOI | 10.2147/cmar.s299020 |
| Pubmed ID | |
| Authors |
Ting Lin, Jinhai Mai, Meng Yan, Zhenhui Li, Xianyue Quan, Xin Chen |
X Demographics
The data shown below were collected from the profiles of 11 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 Kingdom | 2 | 18% |
| Nigeria | 1 | 9% |
| Netherlands | 1 | 9% |
| India | 1 | 9% |
| United States | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 91% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
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 % |
|---|---|---|
| Unspecified | 2 | 15% |
| Student > Ph. D. Student | 2 | 15% |
| Student > Doctoral Student | 1 | 8% |
| Lecturer > Senior Lecturer | 1 | 8% |
| Student > Bachelor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 5 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 2 | 15% |
| Computer Science | 2 | 15% |
| Medicine and Dentistry | 2 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Engineering | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 5 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 April 2021.
All research outputs
#6,716,607
of 24,133,587 outputs
Outputs from Cancer Management and Research
#276
of 2,019 outputs
Outputs of similar age
#143,204
of 423,162 outputs
Outputs of similar age from Cancer Management and Research
#17
of 132 outputs
Altmetric has tracked 24,133,587 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 2,019 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 86% 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 423,162 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 65% of its contemporaries.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.