Corrosion Prediction of Mg Implant using Multiscale Modelling based on Machine Learning Algorithms

Abstract

To improve patient outcomes and reduce the social and financial burdens associated with implant failure, ongoing research and development are essential. For that in this study, MLA has been done to predict the corrosion behavior of Mg implant. This includes advancements in implant materials, surgical techniques, infection prevention strategies, and personalized medicine approaches that consider each patient's unique characteristics. Ultimately, the goal is to make orthopedic surgery safer and more effective. The primary focus is to minimize complications like implant failure due to corrosion to enhance the overall quality of life for patients. Infections around orthopedic implants are a major cause of implant failure. These infections can be challenging to treat because the implant’s presence can make it difficult for the body’s immune system to effectively combat the infection. Preventing infection is crucial and often involves strict sterile procedures during surgery. Antibiotics may also be prescribed prophylactically. Inflammation is a natural response to surgery, but excessive inflammation can cause pain and lead to complications, including implant failure. Advanced materials and improved surgical techniques are designed to reduce the likelihood of aseptic loosening. When an implant fails, revision surgery becomes necessary. Implant materials are chosen to minimize corrosion, but it can still occur. Corrosion can lead to wear and damage to the implant, potentially causing inflammation and implant failure. Surgeons and manufacturers continually seek materials with improved resistance to corrosion.