Opportunities and challenges in the development of artificial intelligence research in spinal surgery

Abstract

Artificial intelligence has emerged as a game-changer in the field of spine surgery, offering transformative diagnostic and therapeutic approaches for spinal conditions. The application of AI in spine research encompasses a diverse range of diseases, with usage scenarios becoming increasingly widespread and technological integration going deeper. AI technology shows immense promise and value in the diagnosis of spinal diseases, the formulation of treatment strategies, surgical navigation, prognostic evaluation, and postoperative rehabilitation. Through deep learning and machine learning, AI can aid doctors in enhancing diagnostic accuracy, creating personalized treatment plans, and executing precise maneuvers during surgery, thus improving operational safety. Moreover, AI can provide intelligent support for patients' postoperative recovery, facilitating the restoration of their functions. However, current research is still in its nascent stage and confronts several challenges, such as the lack of standardized databases, the simplicity of algorithmic learning models, the inadequate fusion of multi-modal clinical information, and the limited clinical applicability. By developing open-source, standardized spine databases, incorporating innovative intelligent core algorithms, and establishing normalized screening, diagnostic, and predictive models for spinal conditions, we trust that we can drive the innovation and refinement of diagnostic and treatment technologies in spine surgery. This will realize an effective conjunction between technological provision and clinical demands, continuously elevating the intelligence level of spine surgery and offering safer, more effective medical services to a vast array of patients.