Pregled bibliografske jedinice broj: 795724
Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease
Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease // BMC medical informatics and decision making, 15 (2015), S3; S1-1 doi:10.1186/1472-6947-15-S3-S1 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 795724 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease
Autori
Badnjević, Almir ; Cifrek, Mario ; Koruga, Dragan ; Osmanković, Dinko
Izvornik
BMC medical informatics and decision making (1472-6947) 15
(2015), S3;
S1-1
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
astma; COPD; neuro-fuzzy classification
Sažetak
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. Additionally, using bronchodilatation and bronhoprovocation tests we get a complete patient’s dynamic assessment, as opposed to the solution that provides a static assessment of the patient.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Mario Cifrek
(autor)
Poveznice na cjeloviti tekst rada:
Pristup cjelovitom tekstu rada doi
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE
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