| Title |
Using machine learning for mortality prediction and risk stratification in atezolizumab‐treated cancer patients: Integrative analysis of eight clinical trials
|
|---|---|
| Published in |
Cancer Medicine, July 2022
|
| DOI | 10.1002/cam4.5060 |
| Pubmed ID | |
| Authors |
Yougen Wu, Wenyu Zhu, Jing Wang, Lvwen Liu, Wei Zhang, Yang Wang, Jindong Shi, Ju Xia, Yuting Gu, Qingqing Qian, Yang Hong |
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 % |
|---|---|---|
| United States | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 2 | 12% |
| Student > Bachelor | 2 | 12% |
| Researcher | 2 | 12% |
| Student > Ph. D. Student | 1 | 6% |
| Student > Postgraduate | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 9 | 53% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 12% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 6% |
| Nursing and Health Professions | 1 | 6% |
| Computer Science | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 10 | 59% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 27 July 2022.
All research outputs
#15,852,362
of 24,156,282 outputs
Outputs from Cancer Medicine
#1,529
of 3,610 outputs
Outputs of similar age
#225,964
of 420,621 outputs
Outputs of similar age from Cancer Medicine
#64
of 187 outputs
Altmetric has tracked 24,156,282 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,610 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 52% 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 420,621 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 187 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 59% of its contemporaries.