| Title |
A cloud computing based 12-lead ECG telemedicine service
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2012
|
| DOI | 10.1186/1472-6947-12-77 |
| Pubmed ID | |
| Authors |
Jui-chien Hsieh, Meng-Wei Hsu |
| Abstract |
Due to the great variability of 12-lead ECG instruments and medical specialists' interpretation skills, it remains a challenge to deliver rapid and accurate 12-lead ECG reports with senior cardiologists' decision making support in emergency telecardiology. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 40% |
| United States | 2 | 40% |
| Argentina | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 4 | 80% |
| Members of the public | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 2% |
| Indonesia | 1 | <1% |
| United Kingdom | 1 | <1% |
| Australia | 1 | <1% |
| Japan | 1 | <1% |
| Canada | 1 | <1% |
| Unknown | 154 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 33 | 20% |
| Student > Ph. D. Student | 30 | 18% |
| Researcher | 14 | 9% |
| Student > Bachelor | 12 | 7% |
| Student > Postgraduate | 11 | 7% |
| Other | 36 | 22% |
| Unknown | 27 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 42 | 26% |
| Medicine and Dentistry | 30 | 18% |
| Engineering | 20 | 12% |
| Business, Management and Accounting | 12 | 7% |
| Nursing and Health Professions | 5 | 3% |
| Other | 23 | 14% |
| Unknown | 31 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 07 August 2013.
All research outputs
#12,857,407
of 22,671,366 outputs
Outputs from BMC Medical Informatics and Decision Making
#875
of 1,978 outputs
Outputs of similar age
#87,258
of 164,530 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#26
of 52 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,978 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 53% 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 164,530 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.