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Toward Digital Periodontal Health: Recent Advances and Future Perspectives
Fatemeh Soheili1,2, Niloufar Delfan1,3, Negin Masoudifar4
1Biologically Inspired Sensors and Actuators Laboratory (BIOSA), Lassonde School of Engineering, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.
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.
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