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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MODILM: towards better complex diseases classification using a novel multi-omics data integration learning model
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, May 2023
|
| DOI | 10.1186/s12911-023-02173-9 |
| Pubmed ID | |
| Authors |
Yating Zhong, Yuzhong Peng, Yanmei Lin, Dingjia Chen, Hao Zhang, Wen Zheng, Yuanyuan Chen, Changliang Wu |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 19% |
| Student > Master | 3 | 19% |
| Researcher | 2 | 13% |
| Professor | 1 | 6% |
| Unspecified | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 4 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 13% |
| Agricultural and Biological Sciences | 2 | 13% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Unspecified | 1 | 6% |
| Environmental Science | 1 | 6% |
| Other | 1 | 6% |
| Unknown | 8 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 July 2023.
All research outputs
#7,769,406
of 24,133,587 outputs
Outputs from BMC Medical Informatics and Decision Making
#769
of 2,061 outputs
Outputs of similar age
#130,947
of 380,773 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#7
of 30 outputs
Altmetric has tracked 24,133,587 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 2,061 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 62% 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 380,773 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 65% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.