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Attention Score in Context
Title |
The development of a combined mathematical model to forecast the incidence of hepatitis E in Shanghai, China
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Published in |
BMC Infectious Diseases, September 2013
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DOI | 10.1186/1471-2334-13-421 |
Pubmed ID | |
Authors |
Hong Ren, Jian Li, Zheng-An Yuan, Jia-Yu Hu, Yan Yu, Yi-Han Lu |
Abstract |
Sporadic hepatitis E has become an important public health concern in China. Accurate forecasting of the incidence of hepatitis E is needed to better plan future medical needs. Few mathematical models can be used because hepatitis E morbidity data has both linear and nonlinear patterns. We developed a combined mathematical model using an autoregressive integrated moving average model (ARIMA) and a back propagation neural network (BPNN) to forecast the incidence of hepatitis E. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 1 | 2% |
Unknown | 40 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 12 | 29% |
Student > Ph. D. Student | 6 | 15% |
Student > Bachelor | 3 | 7% |
Student > Doctoral Student | 2 | 5% |
Lecturer | 2 | 5% |
Other | 7 | 17% |
Unknown | 9 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 17% |
Agricultural and Biological Sciences | 5 | 12% |
Computer Science | 5 | 12% |
Engineering | 3 | 7% |
Environmental Science | 3 | 7% |
Other | 9 | 22% |
Unknown | 9 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 08 September 2013.
All research outputs
#20,200,843
of 22,719,618 outputs
Outputs from BMC Infectious Diseases
#6,442
of 7,659 outputs
Outputs of similar age
#173,027
of 197,573 outputs
Outputs of similar age from BMC Infectious Diseases
#114
of 144 outputs
Altmetric has tracked 22,719,618 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,659 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.5. This one is in the 1st percentile – i.e., 1% 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 197,573 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.