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KMID : 1157520240200010027
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International Journal of Clinical Preventive Dentistry
2024 Volume.20 No. 1 p.27 ~ p.32
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Development of AI Web Service for Quantification of Dental Plaque
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Lee Jae-Young
Lim Ji-Na
Han Byung-Hee
Seok Soo-Hwang
Yoo Hyun-Jun
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Abstract
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Dental plaque may be detected using a plaque disclosing solution. Upon application by a dental professional, the plaque disclosing solution enhances the visibility of dental plaque on the teeth and gingiva for clinical evaluation. This process takes approximately 10 minutes. The scores are subjective and based on professional judgment. Thus, the reliability of the score may be relatively low. Artificial intelligence (AI) and machine learning may improve the objectivity and reliability of dental plaque disclosing, To generate training data for machine learning, large amounts of oral data relating to the detection of dentalplaque over the same area need to be collected. A system was developed to support data storage management, classification, and the creation of training data. The YOLOv7 model was adopted. This AI model demonstrated the best performance in real-time dental plaque detection. Moreover, the related app service facilitates the generation of real-time results from clinical data, and provides a web-based administrative server service that can be used to organize patient data. This study demonstrated that the developed model is effective for dental plaque evaluation.
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KEYWORD
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aritificial intelligence, dental plaque
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