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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine Learning-Based Radiomics Nomogram Using Magnetic Resonance Images for Prediction of Neoadjuvant Chemotherapy Efficacy in Breast Cancer Patients
|
|---|---|
| Published in |
Frontiers in oncology, August 2020
|
| DOI | 10.3389/fonc.2020.01410 |
| Pubmed ID | |
| Authors |
Shujun Chen, Zhenyu Shu, Yongfeng Li, Bo Chen, Lirong Tang, Wenju Mo, Guoliang Shao, Feng Shao |
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 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 48 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 15% |
| Unspecified | 6 | 13% |
| Student > Master | 6 | 13% |
| Student > Doctoral Student | 2 | 4% |
| Other | 2 | 4% |
| Other | 8 | 17% |
| Unknown | 17 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 19% |
| Unspecified | 6 | 13% |
| Engineering | 5 | 10% |
| Biochemistry, Genetics and Molecular Biology | 2 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 20 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 19 September 2020.
All research outputs
#17,628,251
of 25,838,141 outputs
Outputs from Frontiers in oncology
#8,179
of 22,812 outputs
Outputs of similar age
#273,942
of 427,005 outputs
Outputs of similar age from Frontiers in oncology
#217
of 578 outputs
Altmetric has tracked 25,838,141 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,812 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 58% 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 427,005 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 578 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 56% of its contemporaries.