Self-adaptive Bayesian fuzzy inference nets to diagnose cardiovascular diseases

作者: Booma Devi Sekar , Mingchui Dong

DOI: 10.3233/KES-140299

关键词:

摘要: A generalized Bayesian inference nets model (GBINM) to aid developers construct self-adaptive for various applications and a new approach of defining assigning statistical parameters nodes needed calculate propagation probabilities address uncertainties are proposed. GBINM the proposed applied design an intelligent medical system diagnose cardiovascular diseases. Thousands site-sampled clinical data used designing testing such constructed system. The preliminary diagnostic results show that methodology has salient validity effectiveness

参考文章(22)
M. A. Shwe, D. E. Heckerman, M. Henrion, E. J. Horvitz, H. P. Lehmann, G. F. Cooper, B. Middleton, Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base. I. The probabilistic model and inference algorithms. Methods of Information in Medicine. ,vol. 30, pp. 241- 255 ,(1991) , 10.1055/S-0038-1634846
Maurice E. Cohen, Donna L. Hudson, Samuel E. Hudson, The use of consequential reasoning in cancer chemotherapy. Studies in health technology and informatics. ,vol. 84, pp. 1349- 1353 ,(2001)
Björn Falck, Steen Andreassen, Stig K. Andersen, Marianne Woldbye, MUNIN: a causal probabilistic network for interpretation of electromyographic findings international joint conference on artificial intelligence. pp. 366- 372 ,(1987)
Edward H. Shortliffe, William Van Melle, A. Carlisle Scott, Charlotte D. Jacobs, A. Bruce Campbell, Miriam B. Bischoff, ONCOCIN: an expert system for oncology protocol management international joint conference on artificial intelligence. pp. 876- 881 ,(1981)
Kavishwar B. Wagholikar, Ashok W. Deshpande, Fuzzy relation based modeling for medical diagnostic decision support: Case studies International Journal of Knowledge-based and Intelligent Engineering Systems. ,vol. 12, pp. 319- 326 ,(2008) , 10.3233/KES-2008-125-602
Akila Djebbar, Hayet Farida Merouani, Retrieval and adaptation in CBR through Bayesian Network for diagnosis of hepatic pathologies International Journal of Hybrid Intelligent Systems. ,vol. 9, pp. 123- 134 ,(2012) , 10.3233/HIS-2012-0151
F. Azuaje, W. Dubitzky, P. Lopes, N. Black, K. Adamson, X. Wu, J.A. White, Predicting coronary disease risk based on short-term RR interval measurements: a neural network approach Artificial Intelligence in Medicine. ,vol. 15, pp. 275- 297 ,(1999) , 10.1016/S0933-3657(98)00058-X
Booma Devi Sekar, Ming Chui Dong, Jun Shi, Xiang Yang Hu, Fused Hierarchical Neural Networks for Cardiovascular Disease Diagnosis IEEE Sensors Journal. ,vol. 12, pp. 644- 650 ,(2012) , 10.1109/JSEN.2011.2129506
B LI, M DONG, V MANGI, M UN, A novel intelligent sphygmogram analyzer for health monitoring of cardiovascular system Expert Systems With Applications. ,vol. 28, pp. 693- 700 ,(2005) , 10.1016/J.ESWA.2004.12.026