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Mendeley readers
Attention Score in Context
| 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. |
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 % |
|---|---|---|
| Malaysia | 1 | 20% |
| Australia | 1 | 20% |
| United Kingdom | 1 | 20% |
| India | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 53 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 23% |
| Student > Master | 7 | 13% |
| Student > Bachelor | 5 | 9% |
| Professor | 4 | 8% |
| Lecturer | 2 | 4% |
| Other | 6 | 11% |
| Unknown | 17 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 9 | 17% |
| Medicine and Dentistry | 9 | 17% |
| Computer Science | 6 | 11% |
| Nursing and Health Professions | 4 | 8% |
| Mathematics | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 19 | 36% |
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
#13,956,297
of 22,828,180 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,066
of 1,988 outputs
Outputs of similar age
#133,462
of 267,781 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#22
of 37 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,988 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 44th percentile – i.e., 44% 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 267,781 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.