Integrating Artificial Intelligence into Oral Healthcare: Advances in Surgery, Imaging, and Diagnostics
Artificial intelligence; Oral healthcare; Dental imaging; Implant surgery; Oral diagnostics
European Journal of Prosthodontics and Restorative Dentistry (2026) 34(1s), 116–123
AuthorsAbstractThrough assisting with diagnosis and imaging analysis, surgery planning, decision-making, and digital restoration processes, artificial intelligence (AI) is increasingly taking a significant role in oral care. This narrative review evaluates the impact of AI on oral health, especially focusing on advancements in dental imaging, oral diagnostics, and oral or implant surgical operations. Articles on published research, clinical trials, diagnostic accuracy, review articles, and experimental studies of AI models built using radiographs, cone-beam computed tomography (CBCT) imaging, intraoral photography, digital impressions, clinical data, and diagnostics were considered in this review. It was established that machine learning, deep learning, CNN, computer vision, and decision support tools have been used in detecting dental caries, periapical, PDCL, OMA, and anatomical markers. AI helped with CBCT image segmentation, mandibular canal localization, assessment of implant sites, and surgical guide planning and prediction. AI aided in creating digital impressions, CAD/CAM designs, evaluation of restorations, and material choices in prosthodontics and restoration operations. The most reported metrics for performance were accuracy, sensitivity, specificity, area under the curve, precision, recall, F1-score, diagnostic concordance, and efficiency in time management. Overall, AI had proven effective in improving diagnostics, analysing imaging, surgical operations, and clinical processes. However, it required thorough validation, monitoring, clinician supervision, and proper management to ensure patient safety. 1. Introduction In recent years, artificial intelligence (AI) has become a significant technological breakthrough in contemporary dental practice, providing new opportunities for diagnostic, treatment planning, clinical decision making and workflow optimization processes. AI in oral health typically involves AI technologies such as machine learning, deep learning, artificial neural networks, computer vision, and systems for supporting decisions with data. These technologies are intended to process complex clinical and imaging information, identify patterns and support clinicians in their decisionmaking process to make more accurate and efficient decisions. The potential of bringing AI techniques in various domains of dentistry has been reported by a systematic review conducted by Ahmed et al. [1] who found that AI techniques have been widely used in the field of dentistry for diagnosis, prediction, classification, and support for treatment, with the belief that these technologies could enhance both clinical and research outcomes. With the growing trend of dental practices relying on digital records, radiographic imaging, intraoral scanning, CAD/CAM systems, and electronic patient information, the impact of AI on dentistry has grown significantly. These digital tools generate vast amounts of information which can be analysed and interpreted by AI algorithms, aiding clinical interpretation and treatment planning. Ding et al. discussed that AI was •••••••••••••••••••••••••••••••• ejprd.org- Published by Riset Publishing Services LLC.
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