Open Access

REVIEW

A Review of the Application of Artificial Intelligence in Orthopedic Diseases

Xinlong Diao, Xiao Wang^*, Junkang Qin, Qinmu Wu, Zhiqin He, Xinghong Fan

Department of Electrical Engineering, Guizhou University, Guiyang, China

* Corresponding Author: Xiao Wang. Email:

(This article belongs to the Special Issue: Deep Learning in Computer-Aided Diagnosis Based on Medical Image)

Computers, Materials & Continua 2024, 78(2), 2617-2665. https://doi.org/10.32604/cmc.2024.047377

Received 03 November 2023; Accepted 03 January 2024; Issue published 27 February 2024

Abstract

In recent years, Artificial Intelligence (AI) has revolutionized people’s lives. AI has long made breakthrough progress in the field of surgery. However, the research on the application of AI in orthopedics is still in the exploratory stage. The paper first introduces the background of AI and orthopedic diseases, addresses the shortcomings of traditional methods in the detection of fractures and orthopedic diseases, draws out the advantages of deep learning and machine learning in image detection, and reviews the latest results of deep learning and machine learning applied to orthopedic image detection in recent years, describing the contributions, strengths and weaknesses, and the direction of the future improvements that can be made in each study. Next, the paper also introduces the difficulties of traditional orthopedic surgery and the roles played by AI in preoperative, intraoperative, and postoperative orthopedic surgery, scientifically discussing the advantages and prospects of AI in orthopedic surgery. Finally, the article discusses the limitations of current research and technology in clinical applications, proposes solutions to the problems, and summarizes and outlines possible future research directions. The main objective of this review is to inform future research and development of AI in orthopedics.

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