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Mendeley readers
Attention Score in Context
Title |
Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review
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Published in |
BMC Medicine, February 2014
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DOI | 10.1186/1741-7015-12-22 |
Pubmed ID | |
Authors |
Jordana Leitao, Nikita Desai, Lukasz Aleksandrowicz, Peter Byass, Pierre Miasnikof, Stephen Tollman, Dewan Alam, Ying Lu, Suresh Kumar Rathi, Abhishek Singh, Wilson Suraweera, Faujdar Ram, Prabhat Jha |
Abstract |
Computer-coded verbal autopsy (CCVA) methods to assign causes of death (CODs) for medically unattended deaths have been proposed as an alternative to physician-certified verbal autopsy (PCVA). We conducted a systematic review of 19 published comparison studies (from 684 evaluated), most of which used hospital-based deaths as the reference standard. We assessed the performance of PCVA and five CCVA methods: Random Forest, Tariff, InterVA, King-Lu, and Simplified Symptom Pattern. |
X Demographics
The data shown below were collected from the profiles of 2 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 Kingdom | 1 | 50% |
India | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 152 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | <1% |
United States | 1 | <1% |
Switzerland | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 148 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 31 | 20% |
Student > Master | 31 | 20% |
Student > Ph. D. Student | 20 | 13% |
Other | 10 | 7% |
Student > Doctoral Student | 8 | 5% |
Other | 23 | 15% |
Unknown | 29 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 52 | 34% |
Social Sciences | 19 | 13% |
Nursing and Health Professions | 8 | 5% |
Computer Science | 8 | 5% |
Agricultural and Biological Sciences | 6 | 4% |
Other | 18 | 12% |
Unknown | 41 | 27% |
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 03 September 2023.
All research outputs
#7,154,235
of 25,286,324 outputs
Outputs from BMC Medicine
#2,724
of 3,968 outputs
Outputs of similar age
#79,235
of 320,458 outputs
Outputs of similar age from BMC Medicine
#42
of 59 outputs
Altmetric has tracked 25,286,324 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 3,968 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 45.7. This one is in the 30th percentile – i.e., 30% 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 320,458 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 74% of its contemporaries.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.