Predictive Analytics in Dentistry: AI Applications in Frenectomy and Soft Tissue Management

Abstract

Artificial intelligence (AI) in dentistry has revolutionized the field, enhancing diagnostics, treatment planning, and patient care. With the ability to analyze vast datasets quickly, AI aids in the early detection of oral diseases, improving overall efficiency and precision in dental practices. The study aims to predict frenectomy techniques using AI, focusing on the labial frenulum, a band of tissue connecting the upper lip to the gums that can cause discomfort or aesthetic issues. Saveetha Dental College and Hospitals approved a study using 200 intraoral photographs from a database. The study used the Orange Data Mining tool, a machine learning approach that integrates image mining with visual analytics, for interactive data visualizations and model inference. Naive Bayes effectively predicts frenectomy surgical outcomes with a low accuracy rate of $48 \%$. It outperforms Logistic Regression in all metrics, with a higher accuracy rate of $48 \%$. The F1 score balances precision and recall, with Naive Bayes outperforming Logistic Regression in all metrics. Artificial Intelligence (AI) is revolutionizing oral healthcare by predicting frenectomy techniques, offering personalized, efficient solutions based on individual patient characteristics, and enhancing decision-making processes.

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