An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction

	An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction
	Oluwarotimi Williams Samuel; Grace Mojisola Asogbon; Arun Kumar Sangaiah; Peng Fang; Guanglin Li.
刊名	Expert Systems With Applications
	2017
文献子类	期刊论文
英文摘要	Heart failure (HF) has been considered as one of the deadliest human diseases worldwide and the ac- curate prediction of HF risks would be vital for HF prevention and treatment. To predict HF risks, deci- sion support systems based on artificial neural networks (ANN) have been widely proposed in previous studies. Generally, these existing ANN-based systems usually assumed that HF attributes have equal risk contribution to the HF diagnosis. However, several previous investigations have shown that the risk con- tributions of the attributes would be different. Thus the equal risk assumption concept associated with existing ANN methods would not properly reflect the diagnosis status of HF patients. In this study, the commonly used 13 HF attributes were considered and their contributions were determined by an experi- enced cardiac clinician. And Fuzzy analytic hierarchy process (Fuzzy_AHP) technique was used to compute the global weights for the attributes based on their individual contribution. Then the global weights that represent the contributions of the attributes were applied to train an ANN classifier for the prediction of HF risks in patients. The performance of the newly proposed decision support system based on the inte- gration of ANN and Fuzzy_AHP methods was evaluated by using online clinical dataset of 297 HF patients and compared with that of the conventional ANN method. Our result shows that the proposed method could achieve an average prediction accuracy of 91.10%, which is 4.40% higher in comparison to that of the conventional ANN method. In addition, the newly proposed method also had better performance than seven previous methods that reported prediction accuracies in the range of 57.85–89.01%. The improve- ment of the HF risk prediction in the current study might be due to both the various contributions of the HF attributes and the proposed hybrid method. These findings suggest that the proposed method could be used to accurately predict HF risks in the clinic.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/11932]
专题	深圳先进技术研究院_医工所
作者单位	Expert Systems With Applications
推荐引用方式 GB/T 7714	Oluwarotimi Williams Samuel,Grace Mojisola Asogbon,Arun Kumar Sangaiah,et al. An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction[J]. Expert Systems With Applications,2017.
APA	Oluwarotimi Williams Samuel,Grace Mojisola Asogbon,Arun Kumar Sangaiah,Peng Fang,&Guanglin Li..(2017).An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction.Expert Systems With Applications.
MLA	Oluwarotimi Williams Samuel,et al."An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction".Expert Systems With Applications (2017).