Two-class classification: comparative experiments for chronic kidney disease
Over two million of population across worldwide is currently depending on dialysis treatment or a kidney transplant to survive from kidney disease. Therefore, it is imperative for health agencies such as hospitals or insurance companies to predict the probabilities of patients who suffers from c...
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| Format: | Conference or Workshop Item |
| Language: | en |
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2019
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| Online Access: | http://eprints.uthm.edu.my/5138/1/KP%202020%20%28101%29.pdf http://eprints.uthm.edu.my/5138/ http://10.1109/ISCON47742.2019.9036306 |
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| author | Johari, Ahmad Amni Abd Wahab, Mohd Helmy Mustapha, Aida |
| author_facet | Johari, Ahmad Amni Abd Wahab, Mohd Helmy Mustapha, Aida |
| author_sort | Johari, Ahmad Amni |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Over two million of population across worldwide is
currently depending on dialysis treatment or a kidney transplant
to survive from kidney disease. Therefore, it is imperative for
health agencies such as hospitals or insurance companies to
predict the probabilities of patients who suffers from chronic case
of kidney diseases, hence requiring medical attentions. This study
performs a comparative experiment on prediction of chronic
kidney disease via a classification methodology. Two supervised
classification algorithms are used to build the classification model,
which are Two-Class Decision Forest and Two-Class Neural
Networks. Experimental results showed that Neural Network
performed better based on all features but Decision Forest
produced optimal performance with high accuracy, and precision
as compared to Neural Networks and other algorithms from the
literature such as K-Nearest Neighbor, Support Vector Machine,
and Rule Induction. |
| format | Conference or Workshop Item |
| id | my.uthm.eprints-5138 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2019 |
| record_format | eprints |
| spelling | my.uthm.eprints-51382022-01-28T06:57:06Z http://eprints.uthm.edu.my/5138/ Two-class classification: comparative experiments for chronic kidney disease Johari, Ahmad Amni Abd Wahab, Mohd Helmy Mustapha, Aida T Technology (General) QA71-90 Instruments and machines Over two million of population across worldwide is currently depending on dialysis treatment or a kidney transplant to survive from kidney disease. Therefore, it is imperative for health agencies such as hospitals or insurance companies to predict the probabilities of patients who suffers from chronic case of kidney diseases, hence requiring medical attentions. This study performs a comparative experiment on prediction of chronic kidney disease via a classification methodology. Two supervised classification algorithms are used to build the classification model, which are Two-Class Decision Forest and Two-Class Neural Networks. Experimental results showed that Neural Network performed better based on all features but Decision Forest produced optimal performance with high accuracy, and precision as compared to Neural Networks and other algorithms from the literature such as K-Nearest Neighbor, Support Vector Machine, and Rule Induction. 2019 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/5138/1/KP%202020%20%28101%29.pdf Johari, Ahmad Amni and Abd Wahab, Mohd Helmy and Mustapha, Aida (2019) Two-class classification: comparative experiments for chronic kidney disease. In: 2019 4th International Conference on Information Systems and Computer Networks (ISCON), 21-22 Nov. 2019, Mathura, India. http://10.1109/ISCON47742.2019.9036306 |
| spellingShingle | T Technology (General) QA71-90 Instruments and machines Johari, Ahmad Amni Abd Wahab, Mohd Helmy Mustapha, Aida Two-class classification: comparative experiments for chronic kidney disease |
| title | Two-class classification: comparative experiments for chronic kidney disease |
| title_full | Two-class classification: comparative experiments for chronic kidney disease |
| title_fullStr | Two-class classification: comparative experiments for chronic kidney disease |
| title_full_unstemmed | Two-class classification: comparative experiments for chronic kidney disease |
| title_short | Two-class classification: comparative experiments for chronic kidney disease |
| title_sort | two-class classification: comparative experiments for chronic kidney disease |
| topic | T Technology (General) QA71-90 Instruments and machines |
| url | http://eprints.uthm.edu.my/5138/1/KP%202020%20%28101%29.pdf http://eprints.uthm.edu.my/5138/ http://10.1109/ISCON47742.2019.9036306 |
| url_provider | http://eprints.uthm.edu.my/ |