Authors : Dr. Amar Singh; Dr. Aswathy Haridas; Dr. Vandana Shenoy; Dr. Mohamed Afradh

Volume/Issue : Volume 9 - 2024, Issue 10 - October

Google Scholar : https://tinyurl.com/2vyvcj4h

Scribd : https://tinyurl.com/3ud6vwtw

DOI : https://doi.org/10.38124/ijisrt/IJISRT24OCT105

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Objective: To provide a comprehensive overview of current applications and future prospects of artificial intelligence (AI) in oral and maxillofacial surgery (OMFS), while critically analyzing implementation challenges and exploring potential advancements.  Methods A systematic literature review was conducted using PubMed/MEDLINE and Embase databases, encompassing English-language articles up to December 30, 2023. Search terms combined OMFS and AI concepts, with database-specific syntax employed.  Results AI applications in OMFS span multiple domains, including image analysis, surgical planning, intraoperative guidance, and clinical decision support. Deep learning models have demonstrated high accuracy in detecting mandibular fractures, performing cephalometric analyses, and classifying maxillofacial pathologies. AI-enhanced surgical planning and robotic systems show promise in improving precision and outcomes across various OMFS procedures. However, challenges persist in data quality, clinical validation, and seamless workflow integration.  Conclusions AI technologies have the potential to significantly enhance diagnostic accuracy, surgical precision, and treatment outcomes in OMFS. Future research directions include developing multimodal AI systems, advancing AI-powered surgical navigation, and exploring federated learning approaches. Successful implementation of AI in OMFS practice will require collaborative efforts among clinicians, researchers, engineers, and policymakers to address technical, ethical, and regulatory challenges. As these hurdles are overcome, AI is poised to become an integral part of OMFS, augmenting surgical capabilities and elevating patient care standards.

Keywords : Artificial Intelligence, Oral and Maxillofacial Surgery, Deep Learning, Surgical Planning, Image Analysis.

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25. Yin, C.; Qian, B.; Wei, J.; Li, X.; Zhang, X.; Li, Y.; Zheng, Q. Automatic Generation of Medical Imaging Diagnostic Report with Hierarchical Recurrent Neural Network. In Proceedings of the 2019 IEEE International Conference on Data Mining (ICDM), Beijing, China, 8–11 November 2019
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27. Balaban C, Inam W, Kennedy R, Faiella R. The Future of Dentistry: How AI is Transforming Dental Practices. Compend Contin Educ Dent. 2021;42:14-17.
28. Pham TD, Holmes SB, Coulthard P. A review on artificial intelligence for the diagnosis of fractures in facial trauma imaging. Front Artif Intell. 2023;6:1278529.