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Mapping Artificial Intelligence Research in Oral and Maxillofacial Surgery: A Bibliometric Analysis
0
Zitationen
7
Autoren
2026
Jahr
Abstract
AI applications, particularly imaging-driven models and transformer-based architectures, offer practical tools for diagnosis, surgical planning, and prognostic assessment in OMFS. Transfer learning enables effective adaptation of AI models to institution-specific datasets, facilitating personalised patient management. By highlighting emerging opportunities in pathway analysis and outcome prediction, this study informs clinicians of actionable AI strategies, supporting evidence-based integration into routine practice and guiding the adoption of novel computational approaches for improved patient care.
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