UTILIZATION OF ARTIFICIAL INTELLIGENCE FOR PREDICTIVE MODELING IN DENTAL IMPLANTOLOGY

Abstract

Artificial intelligence (AI) is making waves in dentistry, with applications in predicting dental implant success. AI models analyze patient data (X-rays, medical history) to identify factors influencing implant viability. The aim is to identify existing research on the use of AI-based predictive models in dental implants. The following databases were searched: Web of Science, Scopus, Google Scholar, PubMed, and Cochrane Library, using the keywords "Artificial Intelligence," "Dentistry," "Implant," and "Success." The studies were reviewed qualitatively, as quantitative analysis was not feasible due to the lack of specific outcomes and the insufficient number of studies for comparison. Technology has presented dental implantology with many opportunities, and it is through artificial intelligence that it is advancing. AI is being applied to detect potential implant failure patients, prognosis osseointegration, improve implant design, and master planning and also for data analysis to predict early complications. Decision trees, random forests, Artificial Neural Networks (ANN), and Deep Learning (DL) improve diagnostics and treatment planning and introduce a powerful predictive model for a successful implant.