ARTIFICIAL INTELLIGENCE IN SURGICAL RISK PLANNING AND ASSESSMENT IN DENTISTRY

Abstract

The incorporation of artificial intelligence in dentistry has promoted significant advances in surgical planning and risk assessment, especially through automated image analysis, integration of clinical data, and the development of predictive models capable of estimating therapeutic outcomes and possible complications, increasing the predictability and safety of procedures. The objective of this study was to analyze the use of artificial intelligence in surgical planning and risk assessment in dentistry, discussing its applications, limitations, and perspectives for incorporation into clinical practice. This is a qualitative research study developed through a literature review, with analysis of recent studies related to the topic. The results indicate that systems based on machine learning and neural networks have contributed to diagnostic standardization, personalization of therapeutic planning, and estimation of surgical risks, supporting more evidence-based clinical decisions. It is concluded that artificial intelligence has the potential to enhance therapeutic predictability and improve dental surgical planning, provided that its use is accompanied by continuous scientific validation and proper integration into clinical practice.