You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Integration of an interpretable machine learning algorithm to identify early life risk factors of childhood obesity among preterm infants: a prospective birth cohort
|
|---|---|
| Published in |
BMC Medicine, July 2020
|
| DOI | 10.1186/s12916-020-01642-6 |
| Pubmed ID | |
| Authors |
Yuanqing Fu, Wanglong Gou, Wensheng Hu, Yingying Mao, Yunyi Tian, Xinxiu Liang, Yuhong Guan, Tao Huang, Kelei Li, Xiaofei Guo, Huijuan Liu, Duo Li, Ju-Sheng Zheng |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 20% |
| France | 1 | 20% |
| Italy | 1 | 20% |
| United Kingdom | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 40% |
| Members of the public | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 102 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 14% |
| Student > Bachelor | 12 | 12% |
| Student > Master | 9 | 9% |
| Unspecified | 8 | 8% |
| Researcher | 6 | 6% |
| Other | 14 | 14% |
| Unknown | 39 | 38% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 12% |
| Nursing and Health Professions | 11 | 11% |
| Unspecified | 8 | 8% |
| Computer Science | 7 | 7% |
| Psychology | 5 | 5% |
| Other | 13 | 13% |
| Unknown | 46 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 July 2020.
All research outputs
#13,104,104
of 23,220,133 outputs
Outputs from BMC Medicine
#2,760
of 3,494 outputs
Outputs of similar age
#184,442
of 397,220 outputs
Outputs of similar age from BMC Medicine
#85
of 108 outputs
Altmetric has tracked 23,220,133 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,494 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.7. This one is in the 20th percentile – i.e., 20% 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 397,220 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 53% of its contemporaries.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.