Artificial Intelligence and the State of the Art of Orthopedic Surgery

Abstract

Artificial Intelligence (AI) is rapidly transforming healthcare, particularly in orthopedics, by enhancing diagnostic accuracy, surgical planning, and personalized treatment. This review explores current applications of AI in orthopedics, focusing on its contributions to diagnostics and surgical procedures. Key methodologies such as artificial neural networks (ANNs), convolutional neural networks (CNNs), support vector machines (SVMs), and ensemble learning have significantly improved diagnostic precision and patient care. For instance, CNN-based models excel in tasks like fracture detection and osteoarthritis grading, achieving high sensitivity and specificity. In surgical contexts, AI enhances procedures through robotic assistance and optimized preoperative planning, aiding in prosthetic sizing and minimizing complications. Additionally, predictive analytics during postoperative care enable tailored rehabilitation programs that improve recovery times. Despite these advancements, challenges such as data standardization and algorithm transparency hinder widespread adoption. Addressing these issues is crucial for maximizing AI's potential in orthopedic practice. This review emphasizes the synergistic relationship between AI and clinical expertise, highlighting opportunities to enhance diagnostics and streamline surgical procedures, ultimately driving patient-centric care. Level of evidence: V