dc.contributor.author | Hanein Omar, Dr. Mohamed Basma. F.Idris | |
dc.date.accessioned | 2022-01-27T11:11:00Z | |
dc.date.available | 2022-01-27T11:11:00Z | |
dc.date.issued | 2021-11-01 | |
dc.identifier.uri | http://repository.limu.edu.ly/handle/123456789/3564 | |
dc.description.abstract | Abstract: Asthma is a chronic disease that is caused by inflammation of airways. Diagnosis, predication and classification of
asthmatic are one of the major attractive areas of research for decades by using different and recent techniques, however
the main problem of asthma is misdiagnosis. This paper simplifiesand compare between different Artificial Neural Network
techniques used to solve this problem by using different algorithms to getting a high level of accuracy in diagnosis,
prediction, and classification of asthma like: (data mining algorithms, machine learning algorithms, deep machine learning
algorithms), depending and passing through three stages: data acquisition, feature extracting, data classification. According
to the comparison of different techniques the high accuracy achieved by ANN was (98.85%), and the low accuracy of it was
(80%), despite of the accuracy achieved by Support Vector Machine (SVM) was (86%) when used Mel Frequency Cepstral
Coefficient MFCC for feature extraction, while the accuracy was (99.34%) when used Relief for extracting feature. Based in
our comparison we recommend that if the researchers used the same techniques they should to return to previous studies it
to get high accuracy | en_US |
dc.language.iso | en | en_US |
dc.publisher | Hanein Omar Dr. Mohamed Basma. F.Idris | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Artificial Neural Network, Machine Learning, Support Vector Machine, Impulse Oscillometry,Spirometer. | en_US |
dc.title | Comparison between the different Artificial Neural Network(ANN) accuracy in diagnosis of asthm | en_US |
dc.title.alternative | Comparison between the different Artificial Neural Network(ANN) accuracy in diagnosis of asthm | en_US |
dc.type | Other | en_US |