Titlebook: Artificial Intelligence in Dentistry; Kaan Orhan,Rohan Jagtap Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive l

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Applications of Machine Learning and Artificial Intelligence in the COVID-19 Pandemic,t challenges to healthcare systems all around the world. With the rapid spread of the virus, healthcare systems had to adapt and find new ways to manage the spread of the virus, diagnose and treat infected individuals, as well as develop effective treatments and vaccines. To address these challenges

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Medico-Legal Problems of Artificial Intelligence,scientious way will require knowledge of the terminology and types of AI, as well as forward-thinking regarding the ethical and legal implications within the profession. At the outset, all health and biomedical research, whether AI-based or conventional methods, should adhere to the fundamental ethi

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,Deep Learning in Image Processing: Part 1—Types of Neural Networks, Image Segmentation,atment planning. It can be broadly defined as the application of transformations to digital images, typically with the aim of enhancing the image or extracting relevant information from it. Common examples of medical image processing techniques are (1) image ., i.e., the partitioning of images into

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Future Perspectives of Artificial Intelligence in Dentistry,mes. AI’s future applications include the analysis of dental radiographs to detect abnormalities such as cavities, bone loss, and impacted teeth. Additionally, AI can assist dentists in developing personalized treatment plans tailored to each patient’s unique needs. This chapter focuses on the futur

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,Beruf und sozio-ökonomischer Status,viously simulated. Orthodontists should see these digital systems as a tool and should not hesitate to intervene where necessary..This chapter aims to categorize the common study topics focused on artificial intelligence applications in orthodontics and to provide information about the general conce

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https://doi.org/10.1007/978-3-658-12504-2nalized treatment protocols, it suffers from the unavoidable optimization and trial and error steps in production, production inefficiency, long processes, and excessive human effort accompanied by human errors. A possible solution to these disadvantages can be achieved with the use of AI and roboti