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X Demographics
Mendeley readers
Attention Score in Context
Title |
A Machine Learning Based Framework to Identify and Classify Non-alcoholic Fatty Liver Disease in a Large-Scale Population
|
---|---|
Published in |
Frontiers in Public Health, April 2022
|
DOI | 10.3389/fpubh.2022.846118 |
Pubmed ID | |
Authors |
Weidong Ji, Mingyue Xue, Yushan Zhang, Hua Yao, Yushan Wang |
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 % |
---|---|---|
Tanzania, United Republic of | 1 | 25% |
United Kingdom | 1 | 25% |
Switzerland | 1 | 25% |
Unknown | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 30 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 4 | 13% |
Researcher | 3 | 10% |
Student > Doctoral Student | 2 | 7% |
Student > Postgraduate | 2 | 7% |
Student > Master | 2 | 7% |
Other | 3 | 10% |
Unknown | 14 | 47% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 13% |
Computer Science | 4 | 13% |
Nursing and Health Professions | 3 | 10% |
Engineering | 3 | 10% |
Psychology | 1 | 3% |
Other | 1 | 3% |
Unknown | 14 | 47% |
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 05 April 2022.
All research outputs
#14,182,794
of 23,493,900 outputs
Outputs from Frontiers in Public Health
#3,586
of 11,139 outputs
Outputs of similar age
#202,162
of 443,962 outputs
Outputs of similar age from Frontiers in Public Health
#264
of 1,040 outputs
Altmetric has tracked 23,493,900 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,139 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.7. This one has gotten more attention than average, scoring higher than 67% 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 443,962 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 1,040 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 74% of its contemporaries.