| Title |
COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization
|
|---|---|
| Published in |
npj Digital Medicine, April 2021
|
| DOI | 10.1038/s41746-021-00437-0 |
| Pubmed ID | |
| Authors |
Andre Esteva, Anuprit Kale, Romain Paulus, Kazuma Hashimoto, Wenpeng Yin, Dragomir Radev, Richard Socher |
X Demographics
The data shown below were collected from the profiles of 10 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 | 2 | 20% |
| South Africa | 1 | 10% |
| Indonesia | 1 | 10% |
| Unknown | 6 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 80% |
| Practitioners (doctors, other healthcare professionals) | 1 | 10% |
| Scientists | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 179 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 179 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 20 | 11% |
| Student > Ph. D. Student | 18 | 10% |
| Researcher | 13 | 7% |
| Student > Bachelor | 10 | 6% |
| Lecturer | 8 | 4% |
| Other | 27 | 15% |
| Unknown | 83 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 58 | 32% |
| Engineering | 6 | 3% |
| Medicine and Dentistry | 5 | 3% |
| Unspecified | 5 | 3% |
| Agricultural and Biological Sciences | 3 | 2% |
| Other | 14 | 8% |
| Unknown | 88 | 49% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 21 February 2024.
All research outputs
#2,895,073
of 25,775,807 outputs
Outputs from npj Digital Medicine
#618
of 1,031 outputs
Outputs of similar age
#74,103
of 458,381 outputs
Outputs of similar age from npj Digital Medicine
#28
of 49 outputs
Altmetric has tracked 25,775,807 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,031 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.9. This one is in the 40th percentile – i.e., 40% 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 458,381 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.