Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease
Liver Disease is one of the most common diseases which can be prevented by early diagnosis and up-todate treatment. Advances in machine learning and intelligence techniques have led to the effective diagnosis and prediction of diseases to improve the treatment of patients and reduce the cost of treat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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European Alliance for Innovation (EAI)
2019-03-01
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| Series: | EAI Endorsed Transactions on Context-aware Systems and Applications |
| Subjects: | |
| Online Access: | https://eudl.eu/pdf/10.4108/eai.13-7-2018.156838 |
| _version_ | 1811285389305970688 |
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| author | Vahid Hajihashemi Zeinab Hassani Iman Dehmajnoonie Keivan Borna |
| author_facet | Vahid Hajihashemi Zeinab Hassani Iman Dehmajnoonie Keivan Borna |
| author_sort | Vahid Hajihashemi |
| collection | DOAJ |
| description | Liver Disease is one of the most common diseases which can be prevented by early diagnosis and up-todate treatment. Advances in machine learning and intelligence techniques have led to the effective diagnosis and prediction of diseases to improve the treatment of patients and reduce the cost of treatment. Whale Optimization Algorithm is a swarm intelligent technique, inspired by the social behavior of whales. One of the effective classification algorithms is K-Nearest Neighbor which is employed for pattern recognition. This paper was designed to investigate the prediction of Liver Disease using a hybrid algorithm including KNN and WOA. In order to evaluate the efficiency of hybrid algorithm, two datasets of liver disease including BUPA and ILPD were used. The results showed that 81.24% and 91.28% of accuracy was gained by the proposed algorithm for BUPA and ILPD, respectively. Experimental results showed that the hybrid WON-KNN is a better classifier to predict the liver diseases. |
| first_indexed | 2024-04-13T02:43:22Z |
| format | Article |
| id | doaj.art-bac0bf0c86e54c5f99a2a3e6e6f7f609 |
| institution | Directory Open Access Journal |
| issn | 2409-0026 |
| language | English |
| last_indexed | 2024-04-13T02:43:22Z |
| publishDate | 2019-03-01 |
| publisher | European Alliance for Innovation (EAI) |
| record_format | Article |
| series | EAI Endorsed Transactions on Context-aware Systems and Applications |
| spelling | doaj.art-bac0bf0c86e54c5f99a2a3e6e6f7f6092022-12-22T03:06:08ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Context-aware Systems and Applications2409-00262019-03-0161610.4108/eai.13-7-2018.156838Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver diseaseVahid Hajihashemi0Zeinab Hassani1Iman Dehmajnoonie2Keivan Borna3Student Member, IEEEFaculty of computer science, Kosar University of Bojnord, IranScience and Research Branch, Islamic Azad University, Kerman, Iran Faculty of Mathematics and Computer Science, Kharazmi University, Tehran, Iran Liver Disease is one of the most common diseases which can be prevented by early diagnosis and up-todate treatment. Advances in machine learning and intelligence techniques have led to the effective diagnosis and prediction of diseases to improve the treatment of patients and reduce the cost of treatment. Whale Optimization Algorithm is a swarm intelligent technique, inspired by the social behavior of whales. One of the effective classification algorithms is K-Nearest Neighbor which is employed for pattern recognition. This paper was designed to investigate the prediction of Liver Disease using a hybrid algorithm including KNN and WOA. In order to evaluate the efficiency of hybrid algorithm, two datasets of liver disease including BUPA and ILPD were used. The results showed that 81.24% and 91.28% of accuracy was gained by the proposed algorithm for BUPA and ILPD, respectively. Experimental results showed that the hybrid WON-KNN is a better classifier to predict the liver diseases.https://eudl.eu/pdf/10.4108/eai.13-7-2018.156838Whale Optimization AlgorithmK-Nearest Neighbor AlgorithmLiver DiseaseMedical dataEvolutionary algorithm |
| spellingShingle | Vahid Hajihashemi Zeinab Hassani Iman Dehmajnoonie Keivan Borna Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease EAI Endorsed Transactions on Context-aware Systems and Applications Whale Optimization Algorithm K-Nearest Neighbor Algorithm Liver Disease Medical data Evolutionary algorithm |
| title | Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease |
| title_full | Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease |
| title_fullStr | Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease |
| title_full_unstemmed | Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease |
| title_short | Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease |
| title_sort | hybrid algorithms of whale optimization algorithm and k nearest neighbor to predict the liver disease |
| topic | Whale Optimization Algorithm K-Nearest Neighbor Algorithm Liver Disease Medical data Evolutionary algorithm |
| url | https://eudl.eu/pdf/10.4108/eai.13-7-2018.156838 |
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