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Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease

Overview of attention for article published in BMC Medical Informatics and Decision Making, September 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 tweeters

Citations

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48 Dimensions

Readers on

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43 Mendeley
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Title
Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease
Published in
BMC Medical Informatics and Decision Making, September 2015
DOI 10.1186/1472-6947-15-s3-s1
Pubmed ID
Authors

Almir Badnjevic, Mario Cifrek, Dragan Koruga, Dinko Osmankovic

Abstract

This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the trained neural network. Fuzzy rules and neural network parameters are defined according to Global Initiative for Asthma (GINA) and Global Initiative for chronic Obstructive Lung Disease (GOLD) guidelines. For neural network training more than one thousand medical reports obtained from database of the company CareFusion were used. Afterwards the system was validated on 455 patients by physicians from the Clinical Centre University of Sarajevo. Out of 170 patients with asthma, 99.41% of patients were correctly classified. In addition, 99.19% of the 248 COPD patients were correctly classified. The system was 100% successful on 37 patients with normal lung function. Sensitivity of 99.28% and specificity of 100% in asthma and COPD classification were obtained. Our neuro-fuzzy system for classification of asthma and COPD uses a combination of spirometry and Impulse Oscillometry System (IOS) test results, which in the very beginning enables more accurate classification.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 19%
Student > Master 7 16%
Professor 4 9%
Student > Bachelor 3 7%
Researcher 2 5%
Other 5 12%
Unknown 14 33%
Readers by discipline Count As %
Engineering 8 19%
Medicine and Dentistry 6 14%
Computer Science 5 12%
Nursing and Health Professions 4 9%
Mathematics 2 5%
Other 3 7%
Unknown 15 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 July 2016.
All research outputs
#3,645,060
of 8,029,085 outputs
Outputs from BMC Medical Informatics and Decision Making
#534
of 959 outputs
Outputs of similar age
#89,216
of 219,814 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#17
of 31 outputs
Altmetric has tracked 8,029,085 research outputs across all sources so far. This one has received more attention than most of these and is in the 53rd percentile.
So far Altmetric has tracked 959 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 42nd percentile – i.e., 42% 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 219,814 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 57% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.