Assesment of Second Class Malocclusion with Artificial Intelligence

This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.

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.