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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Machine Learning Methods Applied to Predict Ventilator-Associated Pneumonia with Pseudomonas aeruginosa Infection via Sensor Array of Electronic Nose in Intensive Care Unit
|
|---|---|
| Published in |
Sensors, April 2019
|
| DOI | 10.3390/s19081866 |
| Pubmed ID | |
| Authors |
Yu-Hsuan Liao, Zhong-Chuang Wang, Fu-Gui Zhang, Maysam F. Abbod, Chung-Hung Shih, Jiann-Shing Shieh |
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 % |
|---|---|---|
| Switzerland | 1 | 33% |
| Japan | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 96 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 11% |
| Unspecified | 10 | 10% |
| Student > Ph. D. Student | 10 | 10% |
| Student > Master | 8 | 8% |
| Student > Bachelor | 4 | 4% |
| Other | 12 | 13% |
| Unknown | 41 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 10 | 10% |
| Computer Science | 10 | 10% |
| Engineering | 8 | 8% |
| Medicine and Dentistry | 6 | 6% |
| Nursing and Health Professions | 5 | 5% |
| Other | 12 | 13% |
| Unknown | 45 | 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 16 March 2020.
All research outputs
#16,053,755
of 25,385,509 outputs
Outputs from Sensors
#8,556
of 24,318 outputs
Outputs of similar age
#208,512
of 363,771 outputs
Outputs of similar age from Sensors
#200
of 677 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,318 research outputs from this source. They receive a mean Attention Score of 3.1. 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 363,771 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 677 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 69% of its contemporaries.