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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models
|
|---|---|
| Published in |
Frontiers in Public Health, March 2022
|
| DOI | 10.3389/fpubh.2022.853294 |
| Pubmed ID | |
| Authors |
C. Kavitha, Vinodhini Mani, S. R. Srividhya, Osamah Ibrahim Khalaf, Carlos Andrés Tavera Romero |
X Demographics
The data shown below were collected from the profiles of 3 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 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 236 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 236 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 7% |
| Student > Master | 15 | 6% |
| Student > Bachelor | 11 | 5% |
| Unspecified | 6 | 3% |
| Researcher | 6 | 3% |
| Other | 18 | 8% |
| Unknown | 164 | 69% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 22 | 9% |
| Engineering | 11 | 5% |
| Unspecified | 6 | 3% |
| Neuroscience | 6 | 3% |
| Biochemistry, Genetics and Molecular Biology | 3 | 1% |
| Other | 21 | 9% |
| Unknown | 167 | 71% |
Attention Score in Context
This research output has an Altmetric Attention Score of 38. 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 24 January 2024.
All research outputs
#1,052,268
of 25,223,158 outputs
Outputs from Frontiers in Public Health
#522
of 13,729 outputs
Outputs of similar age
#25,885
of 437,388 outputs
Outputs of similar age from Frontiers in Public Health
#38
of 967 outputs
Altmetric has tracked 25,223,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,729 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one has done particularly well, scoring higher than 96% 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 437,388 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 967 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.