Aplicabilidade da inteligência artificial no diagnóstico, planejamento e aquisição de imagens em Tomografia Computadorizada de Feixe Cônico: Revisão de literatura

Abstract

In recent years, artificial intelligence (AI) has become a central topic in healthcare, particularly in dentistry, where its applications in cone-beam computed tomography (CBCT) have been extensively investigated. Given the growing volume of research, the present study conducted a literature review analyzing 101 scientific articles indexed in the PubMed database, published between 2014 and 2025. The selection prioritized studies related to dental diagnosis, treatment planning, and the enhancement of tomographic image quality. The findings reveal a progressive integration of AI into the interpretation of CBCT examinations, resulting in significant improvements in diagnostic accuracy and in the development of more precise therapeutic plans. Although still incipient in clinical settings, the literature indicates that AI can enhance the safety and agility of interventions, even under professional supervision. Despite its potential to improve the quality and efficiency of dental care, challenges remain, such as high implementation costs, the need for professional training, the limited number of studies with broad clinical applicability, and constraints related to the diversity of imaging equipment. Future research should focus on bias mitigation, diversification of AI models, and clinical validation of these technologies to strengthen their practical implementation. The adoption of AI in dental tomography appears promising for promoting more individualized, accurate, and safe diagnoses, representing a transformative advancement in dental practice.