Predicting Corrosion Damage in the Human Body Using Artificial Intelligence: In Vitro Progress and Future
Michael A Kurtz1, Ruoyu Yang2, Mohan S R Elapolu2
1Department of Bioengineering, Clemson University, Clemson, SC, USA; The Clemson University-Medical University of South Carolina Bioengineering Program, 68 President Street, Charleston, SC 29425, USA.
The Orthopedic Clinics of North America
|March 9, 2023
Summary
Artificial intelligence (AI) can enhance orthopedic alloy research by applying models from corrosion science. This review explores AI applications for studying fretting, crevice, and pitting corrosion in orthopedic implants.
Area of Science:
- Materials Science
- Biomedical Engineering
- Computer Science
Background:
- Artificial intelligence (AI) shows promise in clinical settings, but few applications have demonstrably improved patient outcomes.
- Corrosion is a critical factor affecting the longevity and performance of orthopedic implants, particularly those made from titanium and cobalt chrome alloys.
- Existing AI models in non-orthopedic corrosion science offer potential for novel applications in orthopedic research.
Purpose of the Study:
- To explore the applicability of artificial intelligence (AI) models from non-orthopedic corrosion science to the study of orthopedic alloys.
- To bridge the gap between AI advancements and their translation into improved clinical outcomes for orthopedic implants.
- To identify specific AI models suitable for analyzing corrosion mechanisms in orthopedic materials.
Main Methods:
- Systematic literature review of AI applications in corrosion science.
- Review of fundamental AI concepts and models relevant to materials science.
- Analysis of physiologically relevant corrosion damage modes in orthopedic alloys.
- Identification of AI models applicable to fretting, crevice, and pitting corrosion.
Main Results:
- AI models developed in non-orthopedic fields can be adapted for orthopedic alloy research.
- Specific AI models show potential for analyzing complex corrosion phenomena like fretting, crevice, and pitting.
- The review provides a framework for implementing AI in the study of titanium and cobalt chrome alloys.
Conclusions:
- AI holds significant potential to advance the understanding and mitigation of corrosion in orthopedic implants.
- Cross-disciplinary application of AI from corrosion science can accelerate innovation in orthopedic materials.
- Further research integrating AI models is recommended to improve the durability and performance of orthopedic alloys.
