| Title |
Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG
|
|---|---|
| Published in |
Scientific Reports, January 2020
|
| DOI | 10.1038/s41598-019-56927-5 |
| Pubmed ID | |
| Authors |
Mihaela Porumb, Saverio Stranges, Antonio Pescapè, Leandro Pecchia |
X Demographics
The data shown below were collected from the profiles of 261 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 States | 49 | 19% |
| United Kingdom | 19 | 7% |
| France | 11 | 4% |
| Spain | 8 | 3% |
| India | 8 | 3% |
| Mexico | 7 | 3% |
| Canada | 5 | 2% |
| Colombia | 4 | 2% |
| Denmark | 3 | 1% |
| Other | 49 | 19% |
| Unknown | 98 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 176 | 67% |
| Scientists | 53 | 20% |
| Practitioners (doctors, other healthcare professionals) | 26 | 10% |
| Science communicators (journalists, bloggers, editors) | 6 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 302 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 302 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 49 | 16% |
| Researcher | 36 | 12% |
| Student > Master | 29 | 10% |
| Student > Bachelor | 19 | 6% |
| Other | 14 | 5% |
| Other | 50 | 17% |
| Unknown | 105 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 47 | 16% |
| Medicine and Dentistry | 43 | 14% |
| Engineering | 35 | 12% |
| Biochemistry, Genetics and Molecular Biology | 13 | 4% |
| Business, Management and Accounting | 7 | 2% |
| Other | 44 | 15% |
| Unknown | 113 | 37% |
Attention Score in Context
This research output has an Altmetric Attention Score of 413. 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 June 2022.
All research outputs
#72,669
of 25,804,096 outputs
Outputs from Scientific Reports
#985
of 143,111 outputs
Outputs of similar age
#1,679
of 480,224 outputs
Outputs of similar age from Scientific Reports
#30
of 4,366 outputs
Altmetric has tracked 25,804,096 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 143,111 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.8. This one has done particularly well, scoring higher than 99% 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 480,224 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 99% of its contemporaries.
We're also able to compare this research output to 4,366 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 99% of its contemporaries.