| Title |
EHR phenotyping via jointly embedding medical concepts and words into a unified vector space
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, December 2018
|
| DOI | 10.1186/s12911-018-0672-0 |
| Pubmed ID | |
| Authors |
Tian Bai, Ashis Kumar Chanda, Brian L. Egleston, Slobodan Vucetic |
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 % |
|---|---|---|
| United States | 1 | 33% |
| France | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 86 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 21% |
| Researcher | 11 | 13% |
| Student > Master | 8 | 9% |
| Other | 7 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Other | 11 | 13% |
| Unknown | 26 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 16% |
| Computer Science | 14 | 16% |
| Engineering | 9 | 10% |
| Business, Management and Accounting | 3 | 3% |
| Materials Science | 3 | 3% |
| Other | 14 | 16% |
| Unknown | 29 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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
#6,140,209
of 23,117,738 outputs
Outputs from BMC Medical Informatics and Decision Making
#549
of 2,013 outputs
Outputs of similar age
#124,954
of 436,996 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#15
of 51 outputs
Altmetric has tracked 23,117,738 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 2,013 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 72% 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 436,996 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 71% of its contemporaries.
We're also able to compare this research output to 51 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 70% of its contemporaries.