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Titlebook: Applications of Generative AI; Zhihan Lyu Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer N

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Acetylcholinesterase Inhibitorsne. Furthermore, the increasing availability of GPT tools suggests that the synergy between the two will continue to improve research output quality and save time. The key to successful integration lies in the appropriate use of GPT that can be achieved by directing AI tools to solve tasks effectively and using prompt engineering techniques.
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https://doi.org/10.1007/978-1-4020-5614-7ta or latent representations. In this chapter, we provide a practical guide on how generative AI is transforming medical imaging, by reviewing the state-of-the-art methods and frameworks, presenting some successful case studies in different domains and modalities, and discussing the future directions and opportunities for research and development.
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Image Rendering with Generative Adversarial Networks,tic rendering, style transfer, and image synthesis, are discussed, along with the challenges and limitations associated with them. The chapter concludes with an outlook on the future prospects of neural rendering and generative models, emphasizing their potential to revolutionize digital content creation and consumption.
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