Hybrid of swarm intelligent algorithms in medical applications

In this paper, we designed a hybrid of swarm intelligence algorithms to diagnose hepatitis, breast tissue, and dermatology conditions in patients with such infection. The effectiveness of hybrid swarm intelligent algorithms was studied since no single algorithm is effective in solving all types of...

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Main Authors:	Abubakar, Adamu, Haruna, Chiroma, Abdullah Muaz, Sanah, Ya'u Gital, Abdulsalam, Baba Dauda, Ali, Joda Usman, Muhammed
Other Authors:	Abawajy, Jemal H.
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Nature Singapore 2019
Subjects:	Q350 Information theory
Online Access:	http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/1/Proceedings%2Bof%2Bthe%2BInternational%2BConfere.pdf http://irep.iium.edu.my/74294/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_scopus.pdf

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spelling	iium-742942019-10-29T14:24:38Z http://irep.iium.edu.my/74294/ Hybrid of swarm intelligent algorithms in medical applications Abubakar, Adamu Haruna, Chiroma Abdullah Muaz, Sanah Ya'u Gital, Abdulsalam Baba Dauda, Ali Joda Usman, Muhammed Q350 Information theory In this paper, we designed a hybrid of swarm intelligence algorithms to diagnose hepatitis, breast tissue, and dermatology conditions in patients with such infection. The effectiveness of hybrid swarm intelligent algorithms was studied since no single algorithm is effective in solving all types of problems. In this study, feed forward and Elman recurrent neural network (ERN) with swarm intelligent algorithms is used for the classification of the mentioned diseases. The capabilities of six (6) global optimization learning algorithms were studied and their performances in training as well as testing were compared. These algorithms include: hybrid of Cuckoo Search algorithm and Levenberg-Marquardt (LM) (CSLM), Cuckoo Search algorithm (CS) and backpropagation (BP) (CSBP), CS and ERN (CSERN), Artificial Bee Colony (ABC) and LM (ABCLM), ABC and BP (ABCBP), Genetic Algorithm (GA) and BP (GANN). Simulation comparative results indicated that the classification accuracy and run time of the CSLM outperform the CSERN, GANN, ABCBP, ABCLM, and CSBP in the breast tissue dataset. On the other hand, the CSERN performs better than the CSLM, GANN, ABCBP, ABCLM, and CSBP in both the Springer Nature Singapore Abawajy, Jemal H. Othman, Mohamed Ghazali, Rozaida Mat Deris, Mustafa Mahdin, Hairulnizam Herawan, Tutut 2019 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/74294/1/Proceedings%2Bof%2Bthe%2BInternational%2BConfere.pdf application/pdf en http://irep.iium.edu.my/74294/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_scopus.pdf Abubakar, Adamu and Haruna, Chiroma and Abdullah Muaz, Sanah and Ya'u Gital, Abdulsalam and Baba Dauda, Ali and Joda Usman, Muhammed (2019) Hybrid of swarm intelligent algorithms in medical applications. In: The Second International Conference on Advanced Data and Information Engineering (DaEng-2015), 25-26 Apr 2015, Bali, Indonesia. https://link.springer.com/chapter/10.1007/978-981-13-1799-6_63 https://doi.org/10.1007/978-981-13-1799-6_63
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	Q350 Information theory
spellingShingle	Q350 Information theory Abubakar, Adamu Haruna, Chiroma Abdullah Muaz, Sanah Ya'u Gital, Abdulsalam Baba Dauda, Ali Joda Usman, Muhammed Hybrid of swarm intelligent algorithms in medical applications
description	In this paper, we designed a hybrid of swarm intelligence algorithms to diagnose hepatitis, breast tissue, and dermatology conditions in patients with such infection. The effectiveness of hybrid swarm intelligent algorithms was studied since no single algorithm is effective in solving all types of problems. In this study, feed forward and Elman recurrent neural network (ERN) with swarm intelligent algorithms is used for the classification of the mentioned diseases. The capabilities of six (6) global optimization learning algorithms were studied and their performances in training as well as testing were compared. These algorithms include: hybrid of Cuckoo Search algorithm and Levenberg-Marquardt (LM) (CSLM), Cuckoo Search algorithm (CS) and backpropagation (BP) (CSBP), CS and ERN (CSERN), Artificial Bee Colony (ABC) and LM (ABCLM), ABC and BP (ABCBP), Genetic Algorithm (GA) and BP (GANN). Simulation comparative results indicated that the classification accuracy and run time of the CSLM outperform the CSERN, GANN, ABCBP, ABCLM, and CSBP in the breast tissue dataset. On the other hand, the CSERN performs better than the CSLM, GANN, ABCBP, ABCLM, and CSBP in both the
author2	Abawajy, Jemal H.
author_facet	Abawajy, Jemal H. Abubakar, Adamu Haruna, Chiroma Abdullah Muaz, Sanah Ya'u Gital, Abdulsalam Baba Dauda, Ali Joda Usman, Muhammed
format	Conference or Workshop Item
author	Abubakar, Adamu Haruna, Chiroma Abdullah Muaz, Sanah Ya'u Gital, Abdulsalam Baba Dauda, Ali Joda Usman, Muhammed
author_sort	Abubakar, Adamu
title	Hybrid of swarm intelligent algorithms in medical applications
title_short	Hybrid of swarm intelligent algorithms in medical applications
title_full	Hybrid of swarm intelligent algorithms in medical applications
title_fullStr	Hybrid of swarm intelligent algorithms in medical applications
title_full_unstemmed	Hybrid of swarm intelligent algorithms in medical applications
title_sort	hybrid of swarm intelligent algorithms in medical applications
publisher	Springer Nature Singapore
publishDate	2019
url	http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/ http://irep.iium.edu.my/74294/1/Proceedings%2Bof%2Bthe%2BInternational%2BConfere.pdf http://irep.iium.edu.my/74294/7/74294_Hybrid%20of%20Swarm%20Intelligent%20Algorithms%20in%20Medical%20Applications_scopus.pdf
first_indexed	2023-09-18T21:45:14Z
last_indexed	2023-09-18T21:45:14Z
_version_	1777413406056251392

Hybrid of swarm intelligent algorithms in medical applications

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