INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE PRACTICE OF MAXILLOFACIAL SURGERY: DIAGNOSTICS, PLANNING, AND ETHICAL-LEGAL ASPECTS
Abstract
Maxillofacial surgery (MFS) is one of the most complex fields of medicine, where the precision of diagnosis and surgical interventions directly determines functional and aesthetic treatment outcomes. Hundreds of thousands of operations are performed on the maxillofacial region worldwide annually. Traditional methods carry risks of subjective errors and variability in outcomes. According to review data from 2025–2026, artificial intelligence (AI) increases diagnostic accuracy to 90–98%, reduces virtual planning time by 30–50%, and decreases the number of revision surgeries. The relevance of this topic is driven by the rapid development of digital technologies and the growing volume of medical data. AI is already being integrated into maxillofacial surgery practice as a powerful assistant, especially in demand in countries with developing healthcare systems, including Russia and the CIS. A brief history of AI in medicine begins in the 1950s (the Turing test, the Dartmouth Conference). The first medical systems appeared in the 1970s (INTERNIST-1). A breakthrough occurred in the 2010s thanks to deep learning and convolutional neural networks. In MFS, the first applications were noted in 1987, and exponential growth has been observed since 2015–2020. Today, AI is applied at all stages: from diagnosis to postoperative monitoring. The purpose of this review article is to systematize current clinical applications of AI in maxillofacial surgery, analyze ethical and legal challenges, and assess development prospects for the next 5–10 years.