Wahid, Juliana and Al-Mazini, Hassan Fouad Abbas (2018) Classification of Cervical Cancer Using Ant-Miner for Medical Expertise Knowledge Management. In: Knowledge Management International Conference (KMICe) 2018, 25 –27 July 2018, Miri Sarawak, Malaysia.

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Abstract

The fourth most frequent cause of cancer death in women is cervical cancer. No sign can be observed in the early stages of the disease. In addition, cervical cancer diagnosis methods used in health centers are time consuming and costly. Data classification has been widely applied in diagnosis cervical cancer for knowledge acquisition. However, none of existing intelligent methods is comprehensible, and they look like a black box to clinicians. In this paper, an ant colony optimization based classification algorithm, Ant-Miner is applied to analyze the cervical cancer data set. The cervical cancer data set used was obtained from the repository of the University of California, Irvine. The proposed algorithm outperforms the previous approach, support vector machine, in the same domain, in terms of better result of classification accuracy.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN: 9789670910871 Organized by: School of Computing, College of Arts and Sciences, Universiti Utara Malaysia.
Uncontrolled Keywords:	Cervical cancer, ant-miner, data classification
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	28 Nov 2018 01:13
Last Modified:	28 Nov 2018 01:13
URI:	https://repo.uum.edu.my/id/eprint/25261

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