The Use of Artificial Intelligence in Orthopedics: Applications and Limitations of Machine Learning in Diagnosis and Prediction

Abstract

Over the last several years, the impact of Artificial Intelligence on the world and on society has been undeniable. More specifically, a subfield, known as Machine Learning (ML), is driving innovation in a vast variety of fields as it denotes the ability of a machine to identify relationships between data without explicit criteria, emulating a human-like type of learning. Over the last decade, research efforts have also been focused on orthopedics in order to provide help and assistance to surgeons and clinicians in their daily tasks. The purpose of this paper is to serve as a guide by presenting the most recent research and achievements in orthopedics concerning these new technologies, by exposing the main concepts and limitations of different applications, and tackling the main problems concerning both the field and the technology itself. The main ML techniques will be introduced and qualitatively explored, by considering the indexes that better identify the performance of the models; then, the main two applications will be addressed: diagnosis and prediction. Finally, a discussion about the limitations of the studies and technologies will be proposed.

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