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迈向数字化牙周健康:最新进展与未来展望。

Toward Digital Periodontal Health: Recent Advances and Future Perspectives.

作者信息

Soheili Fatemeh, Delfan Niloufar, Masoudifar Negin, Ebrahimni Shahin, Moshiri Behzad, Glogauer Michael, Ghafar-Zadeh Ebrahim

机构信息

Biologically Inspired Sensors and Actuators Laboratory (BIOSA), Lassonde School of Engineering, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.

Department of Biology, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.

出版信息

Bioengineering (Basel). 2024 Sep 18;11(9):937. doi: 10.3390/bioengineering11090937.

Abstract

Periodontal diseases, ranging from gingivitis to periodontitis, are prevalent oral diseases affecting over 50% of the global population. These diseases arise from infections and inflammation of the gums and supporting bones, significantly impacting oral health. The established link between periodontal diseases and systemic diseases, such as cardiovascular diseases, underscores their importance as a public health concern. Consequently, the early detection and prevention of periodontal diseases have become critical objectives in healthcare, particularly through the integration of advanced artificial intelligence (AI) technologies. This paper aims to bridge the gap between clinical practices and cutting-edge technologies by providing a comprehensive review of current research. We examine the identification of causative factors, disease progression, and the role of AI in enhancing early detection and treatment. Our goal is to underscore the importance of early intervention in improving patient outcomes and to stimulate further interest among researchers, bioengineers, and AI specialists in the ongoing exploration of AI applications in periodontal disease diagnosis.

摘要

从牙龈炎到牙周炎的牙周疾病是普遍存在的口腔疾病,影响着全球超过50%的人口。这些疾病源于牙龈和支持骨骼的感染与炎症,对口腔健康有重大影响。牙周疾病与心血管疾病等全身性疾病之间已确立的联系,凸显了它们作为公共卫生问题的重要性。因此,牙周疾病的早期检测和预防已成为医疗保健中的关键目标,特别是通过整合先进的人工智能(AI)技术。本文旨在通过全面综述当前研究,弥合临床实践与前沿技术之间的差距。我们研究了致病因素的识别、疾病进展以及AI在加强早期检测和治疗方面的作用。我们的目标是强调早期干预对改善患者预后的重要性,并激发研究人员、生物工程师和AI专家对在牙周疾病诊断中持续探索AI应用的进一步兴趣。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3bd5/11428937/1829618876c6/bioengineering-11-00937-g001.jpg

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