Fuzzy Cognitive Map based decision support system for thyroid diagnosis management

Knowledge-based systems are the most common type of artificial intelligence in medicine systems in routine clinical use. They contain medical knowledge, usually about a very specifically defined task, and are able to reason with data from individual patients to come up with reasoned conclusions. Although there are many variations, the knowledge within an expert system is typically represented in the form of a set of rules. Fuzzy cognitive map (FCM) is a knowledge based modeling methodology based on exploiting knowledge and experience from experts. It can handle uncertainty and can be constructed basely by expertspsila knowledge.

[1]  C. Stylios,et al.  Novel Architecture for supporting medical decision making of different data types based on Fuzzy Cognitive Map Framework , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  K. Hoshi,et al.  An analysis of thyroid function diagnosis using Bayesian-type and SOM-type neural networks. , 2005, Chemical & pharmaceutical bulletin.

[3]  Chrysostomos D. Stylios,et al.  Modeling complex systems using fuzzy cognitive maps , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[4]  Kemal Polat,et al.  A novel hybrid method based on artificial immune recognition system (AIRS) with fuzzy weighted pre-processing for thyroid disease diagnosis , 2007, Expert Syst. Appl..

[5]  Bill Karakostas,et al.  The use of fuzzy cognitive maps to simulate the information systems strategic planning process , 1999, Inf. Softw. Technol..

[6]  Sushmita Mitra,et al.  Neuro-fuzzy rule generation: survey in soft computing framework , 2000, IEEE Trans. Neural Networks Learn. Syst..

[7]  Ramasamy Uthurusamy,et al.  Data mining and knowledge discovery in databases , 1996, CACM.

[8]  Isak Gath,et al.  Unsupervised Optimal Fuzzy Clustering , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  S. Geva,et al.  Refining Expert Knowledge with an Artificial Neural Network , 1997, ICONIP.

[10]  Olga Kosheleva,et al.  IEEE International Conference on Fuzzy Systems , 1996 .

[11]  Tulay Yildirim,et al.  Diagnosis of thyroid disease using artificial neural network methods , 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

[12]  M. Shamim Khan,et al.  A Framework for Fuzzy Rule-Based Cognitive Maps , 2004, PRICAI.

[13]  Li-Min Fu,et al.  Knowledge-based connectionism for revising domain theories , 1993, IEEE Trans. Syst. Man Cybern..

[14]  Jude W. Shavlik,et al.  Extracting Refined Rules from Knowledge-Based Neural Networks , 1993, Machine Learning.

[15]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[16]  Massimo Bertolini,et al.  Assessment of human reliability factors: A fuzzy cognitive maps approach , 2007 .

[17]  Lakhmi C. Jain,et al.  Soft Computing Techniques in Knowledge-Based Intelligent Engineering Systems: Approaches and Applications , 1997 .

[18]  Witold Pedrycz,et al.  A Framework for a Novel Scalable FCM Learning Method , 2007 .

[19]  Panagiota Spyridonos,et al.  Advanced soft computing diagnosis method for tumour grading , 2006, Artif. Intell. Medicine.

[20]  Fevzullah Temurtas,et al.  A comparative study on thyroid disease diagnosis using neural networks , 2009, Expert Syst. Appl..

[21]  Jerry M. Mendel,et al.  Generating fuzzy rules by learning from examples , 1992, IEEE Trans. Syst. Man Cybern..

[22]  Rudolf Kruse,et al.  Obtaining interpretable fuzzy classification rules from medical data , 1999, Artif. Intell. Medicine.

[23]  Zahir Irani,et al.  Exploring Fuzzy Cognitive Mapping for IS Evaluation , 2006, Eur. J. Oper. Res..

[24]  Didier Dubois,et al.  Merging Fuzzy Information , 1999 .

[25]  Lukasz A. Kurgan,et al.  A survey of Knowledge Discovery and Data Mining process models , 2006, The Knowledge Engineering Review.

[26]  Sankar K. Pal,et al.  Logical operation based fuzzy MLP for classification and rule generation , 1994, Neural Networks.

[27]  Huan Liu,et al.  X2R: a fast rule generator , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[28]  Chrysostomos D. Stylios,et al.  An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps , 2003, IEEE Transactions on Biomedical Engineering.

[29]  Zhi-Qiang Liu,et al.  On causal inference in fuzzy cognitive maps , 2000, IEEE Trans. Fuzzy Syst..

[30]  Elpiniki I. Papageorgiou,et al.  A weight adaptation method for fuzzy cognitive map learning , 2005, Soft Comput..

[31]  Guoqing Chen,et al.  Fuzzy association rules and the extended mining algorithms , 2002, Inf. Sci..

[32]  Victor L. Berardi,et al.  An investigation of neural networks in thyroid function diagnosis , 1998, Health care management science.

[33]  Chunyan Miao,et al.  Dynamical cognitive network - an extension of fuzzy cognitive map , 2001, IEEE Trans. Fuzzy Syst..