Artificial Intelligence in Periodontal Disease Prediction: A New Frontier in Dental Diagnostics

Abstract: Periodontal disease, a chronic inflammatory condition affecting the supporting structures of the teeth, is a leading cause of tooth loss and is closely associated with systemic conditions such as diabetes and cardiovascular disease. Early diagnosis and accurate prediction of disease progression are critical for effective treatment and prevention. In recent years, artificial intelligence (AI) has emerged as a powerful tool in healthcare, demonstrating potential in enhancing diagnostic precision and predictive capabilities in periodontal care. This article provides a comprehensive overview of AI applications in predicting periodontal disease, focusing on machine learning (ML), deep learning (DL), and neural networks. It explores various datasets, clinical parameters, and imaging modalities used to train AI models, such as radiographs, periodontal probing depths, and microbial profiles. The article also reviews recent advancements in AI-based prediction models, their performance metrics (accuracy, sensitivity, specificity), and clinical applicability. Furthermore, it discusses challenges including data standardization, ethical considerations, model interpretability, and integration into existing dental practice workflows. The findings suggest that AI, when properly validated and integrated, can significantly improve early detection, risk assessment, and personalized treatment planning in periodontal care, ultimately leading to better patient outcomes and resource optimization.

Artificial Intelligence (AI), Periodontal Disease, Machine Learning, Deep Learning, Predictive Modeling, Dental Radiographs, Oral Health, Risk Assessment, Neural Networks, Clinical Decision Support Systems

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