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P. Valerio, F. N. Oktar, G. Goller, S. Ozyegin, A. P. M. Shainberg, A.M. Goes and M.F. Leite, “Biocompatibility evaluation of lithium-hydroxyapatite composite,” Key Engineer Materials, Vol. 309-311, 2006, pp. 1121-1124. doi:10.4028/www.scientific.net/KEM.309-311.1121

has been cited by the following article:

• TITLE: Predicting the Mechanical Properties of BHA-Li2O Composites Using Artificial Neural Networks

  AUTHORS: Hasan Huseyin Celik, Oguzhan Gunduz, Nazmi Ekren, Zeeshan Ahmad, Faik Nuzhet Oktar

  KEYWORDS: Artificial Neural Network, Hydroxyapatite, Li2O Composites, Bioceramic

  JOURNAL NAME: Journal of Biomaterials and Nanobiotechnology, Vol.2 No.1, January 27, 2011

  ABSTRACT: In this study the mechanical properties of bovine hydroxyapatite (BHA)-Li2O composites are predicted using artificial neural networks (ANN) and then compared with obtained experimental values. BHA was mixed with lithium carbonate (Li2CO3) and sintered at various temperatures between 900-1300°C. Selected experimental values obtained for the compression strength, microhardness and density were used to define and train the ANN system. Intermediate data values not used to train the ANN model were then used to compare and determine the reliability of the ANN system. The results demonstrate the viable potential in using the ANN approach in predicting mechanical properties even with limited data sets.