Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method

doi:10.1007/s00500-018-3643-6

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 多媒体计算与图形学团队

	Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method
	Ahmad, Waheed 1; Ahmad, Ayaz 8,9; Iqbal, Amjad 7; Hamayun, Muhammad 6; Hussain, Anwar 6; Rehman, Gauhar 5; Khan, Salman 4; Khan, Ubaid Ullah 3; Khan, Dawar 2; Huang, Lican 1
刊名	SOFT COMPUTING
	2019-11-01
卷号	23 期号:21 页码:10931-10938
关键词	Information gain (IG) The adaptive neuro-fuzzy inference system (ANFIS) Hepatitis Diagnosis Machine learning
ISSN号	1432-7643
DOI	10.1007/s00500-018-3643-6
通讯作者	Ahmad, Waheed(ahdwaheed@hotmail.com) ; Huang, Lican(licanhuang@zstu.edu.cn)
英文摘要	Hepatitis, a common liver inflammation, is one of the major public health issues around the world. Proper interpretation of clinical data for the diagnosis of hepatitis is an important problem that needs to be addressed. In this study, a hybrid intelligent approach, combining information gain method and adaptive neuro-fuzzy inference system (ANFIS), is proposed for the diagnosis of fatal hepatitis disorder. Initially, the hepatitis dataset obtained from the University of California Irvine machine learning repository is preprocessed to make it suitable for the mining process. After the preprocessing stage, information gain method is applied to condense the number of features in order to decrease computation time and classification complexity. Selected features are then fed into the ANFIS classifier system. The performance of the proposed approach was evaluated using statistical methods, and the highest results for the classification accuracy, specificity, and sensitivity analysis of the proposed system reached were 95.24%, 91.7%, and 96.17%, respectively. The obtained results show that the proposed intelligent system has a good diagnosis performance and can be applied as a promising tool for the diagnosis of hepatitis.
WOS关键词	DISEASE DIAGNOSIS ; COMPONENT ANALYSIS ; K-NN ; NETWORK ; ANFIS
WOS研究方向	Computer Science
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000492901800024
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28844]
专题	自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者	Ahmad, Waheed; Huang, Lican
作者单位	1.Zhejiang Sci Tech Univ, Sch Informat, Dept Comp Sci, Hangzhou, Zhejiang, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 3.Comsats Inst Informat Technol Abbottabad, Dept Comp Sci, Islamabad, Pakistan 4.Abdul Wali Khan Univ Mardan, Dept Comp Sci, Mardan, Pakistan 5.Abdul Wali Khan Univ Mardan, Dept Zool, Mardan 23200, Pakistan 6.Abdul Wali Khan Univ Mardan, Dept Bot, Mardan 23200, Pakistan 7.Abdul Wali Khan Univ Mardan, Dept Agr, Mardan, Pakistan 8.Abdul Wali Khan Univ Mardan, Dept Biotechnol, Mardan, Pakistan 9.Chinese Acad Sci, Inst Genet & Dev Biol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Ahmad, Waheed,Ahmad, Ayaz,Iqbal, Amjad,et al. Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method[J]. SOFT COMPUTING,2019,23(21):10931-10938.
APA	Ahmad, Waheed.,Ahmad, Ayaz.,Iqbal, Amjad.,Hamayun, Muhammad.,Hussain, Anwar.,...&Huang, Lican.(2019).Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method.SOFT COMPUTING,23(21),10931-10938.
MLA	Ahmad, Waheed,et al."Intelligent hepatitis diagnosis using adaptive neuro-fuzzy inference system and information gain method".SOFT COMPUTING 23.21(2019):10931-10938.