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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predictive model and feature importance for early detection of type II diabetes mellitus
|
|---|---|
| Published in |
Translational Medicine Communications, August 2021
|
| DOI | 10.1186/s41231-021-00096-z |
| Authors |
Eric Adua, Emmanuel Awuni Kolog, Ebenezer Afrifa-Yamoah, Bright Amankwah, Christian Obirikorang, Enoch Odame Anto, Emmanuel Acheampong, Wei Wang, Antonia Yarney Tetteh |
X Demographics
The data shown below were collected from the profiles of 2 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 Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
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 > Doctoral Student | 3 | 10% |
| Lecturer | 3 | 10% |
| Unspecified | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Student > Master | 2 | 7% |
| Other | 7 | 23% |
| Unknown | 11 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 20% |
| Unspecified | 3 | 10% |
| Engineering | 3 | 10% |
| Nursing and Health Professions | 3 | 10% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 10 | 33% |
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 02 December 2021.
All research outputs
#14,555,398
of 23,310,485 outputs
Outputs from Translational Medicine Communications
#35
of 83 outputs
Outputs of similar age
#215,167
of 430,490 outputs
Outputs of similar age from Translational Medicine Communications
#3
of 6 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 83 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 56% 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 430,490 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.