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Using Artificial Neural Networks in Designing and Developing Magnesium-Based Materials for Degradable Implant Applications
Abstract
In spite of its excellent biocompatibility and nontoxicity, Mg suffers from its uncontrolled degradation as an implant material when exposed to corroding bio-environment. Several parameters including chemical composition, surface properties, microstructural features, processing methods and the exposed environment are the important factors which effect the life span and sustainability of Mg implants in highly corroding bio-environment. Striking a balance among them to yield optimized performance in Mg implants is challenging. Here comes the advantage of using artificial neural networks (ANNs) in designing appropriate chemical composition and other influencing parameters. The present chapter provides a brief summary of using ANN to tailor Mg based implants with promising expected outcomes. Different ANN techniques used to develop Mg based biomaterials are summarized and the challenges involved in implementing ANN techniques in developing Mg based implants are also discussed.
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