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Computational Intelligence and Neuroscience
Volume 2012, Article ID 809235, 8 pages
http://dx.doi.org/10.1155/2012/809235
Research Article

Prediction of the Setting Properties of Calcium Phosphate Bone Cement

Department of Mechanical Engineering, Babol Noshirvani University of Technology, Mazandaran, Babol 47148-71167, Iran

Received 14 March 2012; Revised 15 May 2012; Accepted 24 May 2012

Academic Editor: Shinichi Tamura

Copyright © 2012 Seyed Mahmud Rabiee and Hamid Baseri. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Setting properties of bone substitutes are improved using an injectable system. The injectable bone graft substitutes can be molded to the shape of the bone cavity and set in situ when injected. Such system is useful for surgical operation. The powder part of the injectable bone cement is included of β-tricalcium phosphate, calcium carbonate, and dicalcium phosphate and the liquid part contains poly ethylene glycol solution with different concentrations. In this way, prediction of the mechanical properties, setting times, and injectability helps to optimize the calcium phosphate bone cement properties. The objective of this study is development of three different adaptive neurofuzzy inference systems (ANFISs) for estimation of compression strength, setting time, and injectability using the data generated based on experimental observations. The input parameters of models are polyethylene glycol percent and liquid/powder ratio. Comparison of the predicted values and measured data indicates that the ANFIS model has an acceptable performance to the estimation of calcium phosphate bone cement properties.