ASSESMENT OF SECOND CLASS MALOCCLUSION WITH ARTIFICIAL INTELLIGENCE - Ruziev, Sherzodbek
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Recent advancements in artificial intelligence (AI) have shown promise in the field of dentistry, particularly in the classification of malocclusion. Sabri (2023) developed a system using convolutional neural networks (CNN) and knowledge-based systems (KBS) to classify malocclusion based on the Index of Orthodontic Treatment Need (IOTN). This system achieved an accuracy of 61.20% and could potentially be improved in the future. The use of AI in healthcare, including dentistry, has been further discussed by Jones (2018), who highlighted the potential of AI in transforming medicine. However, the…mehr

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Produktbeschreibung
Recent advancements in artificial intelligence (AI) have shown promise in the field of dentistry, particularly in the classification of malocclusion. Sabri (2023) developed a system using convolutional neural networks (CNN) and knowledge-based systems (KBS) to classify malocclusion based on the Index of Orthodontic Treatment Need (IOTN). This system achieved an accuracy of 61.20% and could potentially be improved in the future. The use of AI in healthcare, including dentistry, has been further discussed by Jones (2018), who highlighted the potential of AI in transforming medicine. However, the specific application of AI in the treatment of malocclusion, particularly second class malocclusion, remains an area for further research.
Autorenporträt
Ruziev Sherzodbek licenciou-se no Liceu Académico n.º 2 do Instituto Médico Estatal de Andijan em 2016 e, no mesmo ano, foi aceite para estudar na Faculdade de Medicina Dentária do Instituto Médico Estatal de Andijan, licenciando-se em 2021. Em 2022, concluiu o mestrado no Instituto Médico Estatal de Tashkent.