Document Type
Article
Publication Date
7-2023
Publication Title
Orthopedic Clinics of North America
Volume
54
Issue
2
Publisher
Elsevier
DOI
https://doi.org/10.1016/j.ocl.2022.11.004
Abstract
Artificial intelligence (AI) is used in the clinic to improve patient care. While the successes illustrate the impact AI can have, few studies have led to improved clinical outcomes. A gap in translational studies, beginning at the basic science level, exists. In this review, we focus on how AI models implemented in non-orthopedic fields of corrosion science may apply to the study of orthopedic alloys. We first define and introduce fundamental AI concepts and models, as well as physiologically relevant corrosion damage modes. We then systematically review the corrosion/AI literature. Finally, we identify several AI models that may be Preprint implemented to study fretting, crevice, and pitting corrosion of titanium and cobalt chrome alloys.
Recommended Citation
Kurtz, Michael A.; Yang, Ruoyu; Elapolu, Mohan S. R.; Wessinger, Audrey C.; Nelson, William; Alaniz, Kazzandra; Rai, Rahul; and Gilbert, Jeremy L., "Predicting Corrosion Damage in the Human Body Using Artificial Intelligence: In Vitro Progress and Future Applications Applications" (2023). Publications. 23.
https://open.clemson.edu/bioengineering_pubs/23
Comments
The published version of this article can be found here: https://www.sciencedirect.com/science/article/abs/pii/S0030589822001730?via%3Dihub