Abstract

Artificialintelligence(AI)hasemergedasatransformativetechnologyinhealthcare, offering unprecedented opportunities for improving diagnosis, treatment planning, prognosis, and personalized patient care. In periodontology, AI applications have expanded rapidly owing to advances in machine learning (ML), deep learning (DL), computer vision, and natural language processing. These technologies facilitate the analysis of complex clinical, radiographic, microbiological, and genetic datasets, thereby supporting clinicians in making evidence-based decisions. AI-driven systems have demonstrated promising accuracy in detecting periodontal bone loss, classifying periodontitis, predicting disease progression, and evaluating treatment outcomes. Furthermore, integration of AI with digital dentistry and precision medicine may enhance individualized periodontal care. Despite these advantages, challenges such as limited dataset diversity, lack of external validation, ethical concerns, algorithmic bias, and regulatory issues continue to impede widespread clinical adoption. This narrative review discusses the fundamental concepts of AI, current applications in periodontology, limitations of existing evidence, and future directions for research and clinical implementation.

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