| Title |
An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients*
|
|---|---|
| Published in |
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 2019
|
| DOI | 10.1109/embc.2019.8856889 |
| Pubmed ID | |
| Authors |
Ya Lu, Thomai Stathopoulou, Maria F. Vasiloglou, Stergios Christodoulidis, Beat Blum, Thomas Walser, Vinzenz Meier, Zeno Stanga, Stavroula G. Mougiakakou |
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 % |
|---|---|---|
| Japan | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 25 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 3 | 12% |
| Student > Master | 3 | 12% |
| Student > Bachelor | 2 | 8% |
| Student > Ph. D. Student | 2 | 8% |
| Professor | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 11 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 16% |
| Nursing and Health Professions | 3 | 12% |
| Computer Science | 2 | 8% |
| Medicine and Dentistry | 2 | 8% |
| Unspecified | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 12 | 48% |
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 04 February 2020.
All research outputs
#16,733,516
of 25,385,509 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#2,122
of 4,377 outputs
Outputs of similar age
#219,933
of 363,724 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#135
of 311 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,377 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 49th percentile – i.e., 49% of its peers scored the same or lower than it.
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 363,724 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 311 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 55% of its contemporaries.