| Title |
Machine learning based on blood test biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy
|
|---|---|
| Published in |
BMJ Oncology, February 2024
|
| DOI | 10.1136/bmjonc-2023-000128 |
| Authors |
Jian-Guo Zhou, Jie Yang, Haitao Wang, Ada Hang-Heng Wong, Fangya Tan, Xiaofei Chen, Si-Si He, Gang Shen, Yun-Jia Wang, Benjamin Frey, Rainer Fietkau, Markus Hecht, Wenzhao Zhong, Hu Ma, Udo Gaipl |
X Demographics
The data shown below were collected from the profiles of 9 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 | 3 | 33% |
| United Kingdom | 2 | 22% |
| United States | 1 | 11% |
| Unknown | 3 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 44% |
| Scientists | 3 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 11% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 17% |
| Student > Ph. D. Student | 1 | 17% |
| Researcher | 1 | 17% |
| Unknown | 3 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 17% |
| Materials Science | 1 | 17% |
| Medicine and Dentistry | 1 | 17% |
| Unknown | 3 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 12 March 2024.
All research outputs
#5,392,768
of 25,698,912 outputs
Outputs from BMJ Oncology
#34
of 59 outputs
Outputs of similar age
#76,926
of 342,590 outputs
Outputs of similar age from BMJ Oncology
#14
of 24 outputs
Altmetric has tracked 25,698,912 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 59 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 66.3. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 342,590 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.