Machine Learning Application to Predict the Degradation Rate of Biomedical Implants

Abstract

Bone repair biomedical materials and tissue engineering are widely applied in the medical field due to their ability to repair bone deficiencies and replace hard tissues. Biodegradable materials are used clinically worldwide because they prevent the need for secondary surgery. In recent decades, biodegradable materials have shown improved chemical, biological and mechanical properties. Biological properties such as degradation rate, while determining the healing process, must match with the mechanical properties also. Biodegradable materials are used in designing bone fracture implants that help in the bone healing process, which has become an interesting area of research. In this work, machine learning is applied to predict the properties of different materials and their degradation rate. This model also automatically generates the composition of biodegradable materials along with their mechanical and biological properties, which saves time taken while performing experimental analysis, and their subsequent failures.