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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Elucidation of the Application of Blood Test Biomarkers to Predict Immune-Related Adverse Events in Atezolizumab-Treated NSCLC Patients Using Machine Learning Methods
|
|---|---|
| Published in |
Frontiers in immunology, June 2022
|
| DOI | 10.3389/fimmu.2022.862752 |
| Pubmed ID | |
| Authors |
Jian-Guo Zhou, Ada Hang-Heng Wong, Haitao Wang, Fangya Tan, Xiaofei Chen, Su-Han Jin, Si-Si He, Gang Shen, Yun-Jia Wang, Benjamin Frey, Rainer Fietkau, Markus Hecht, Hu Ma, Udo S. Gaipl |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 50% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
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 | 3 | 23% |
| Researcher | 3 | 23% |
| Student > Ph. D. Student | 2 | 15% |
| Professor | 1 | 8% |
| Unknown | 4 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 3 | 23% |
| Medicine and Dentistry | 2 | 15% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Computer Science | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 4 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 20 July 2022.
All research outputs
#7,917,115
of 24,115,737 outputs
Outputs from Frontiers in immunology
#9,574
of 28,592 outputs
Outputs of similar age
#147,444
of 426,532 outputs
Outputs of similar age from Frontiers in immunology
#544
of 1,976 outputs
Altmetric has tracked 24,115,737 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 28,592 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 66% 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 426,532 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 1,976 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 72% of its contemporaries.