Sillmann Y M, Monteiro J L G C, Eber P, Baggio A M P, Peacock Z S, Guastaldi F P S
Division of Oral and Maxillofacial Surgery, Massachusetts General Hospital, and Department of Oral and Maxillofacial Surgery, Harvard School of Dental Medicine, Boston, MA, USA.
Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Int J Oral Maxillofac Surg. 2025 Feb;54(2):179-190. doi: 10.1016/j.ijom.2024.09.004. Epub 2024 Sep 27.
Artificial Intelligence (AI) can enhance the precision and efficiency of diagnostics and treatments in oral and maxillofacial surgery (OMS), leveraging advanced computational technologies to mimic intelligent human behaviors. The study aimed to examine the current state of AI in the OMS literature and highlight the urgent need for further research to optimize AI integration in clinical practice and enhance patient outcomes. A scoping review of journals related to OMS focused on OMS-related applications. PubMed was searched using terms "artificial intelligence", "convolutional networks", "neural networks", "machine learning", "deep learning", and "automation". Ninety articles were analyzed and classified into the following subcategories: pathology, orthognathic surgery, facial trauma, temporomandibular joint disorders, dentoalveolar surgery, dental implants, craniofacial deformities, reconstructive surgery, aesthetic surgery, and complications. There was a significant increase in AI-related studies published after 2019, 95.6% of the total reviewed. This surge in research reflects growing interest in AI and its potential in OMS. Among the studies, the primary uses of AI in OMS were in pathology (e.g., lesion detection, lymph node metastasis detection) and orthognathic surgery (e.g., surgical planning through facial bone segmentation). The studies predominantly employed convolutional neural networks (CNNs) and artificial neural networks (ANNs) for classification tasks, potentially improving clinical outcomes.
人工智能(AI)可以利用先进的计算技术来模仿人类的智能行为,从而提高口腔颌面外科(OMS)诊断和治疗的精度与效率。本研究旨在审视OMS文献中AI的现状,并强调迫切需要进一步开展研究,以优化AI在临床实践中的整合并改善患者预后。一项针对与OMS相关期刊的范围综述聚焦于与OMS相关的应用。使用 “人工智能”“卷积网络”“神经网络”“机器学习”“深度学习” 和 “自动化” 等术语在PubMed上进行检索。对90篇文章进行了分析,并将其分类为以下子类别:病理学、正颌外科、面部创伤、颞下颌关节紊乱、牙槽外科、牙种植体、颅面畸形、重建外科、美容外科和并发症。2019年之后发表的与AI相关的研究显著增加,占总综述量的95.6%。这一研究热潮反映出对AI及其在OMS中的潜力的兴趣日益浓厚。在这些研究中,AI在OMS中的主要用途是病理学(例如病变检测、淋巴结转移检测)和正颌外科(例如通过面部骨骼分割进行手术规划)。这些研究主要采用卷积神经网络(CNN)和人工神经网络(ANN)进行分类任务,有可能改善临床结果。
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