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Enables readers to understand the future of medical applications with generative AI and related applications
Generative Artificial Intelligence for Biomedical and Smart Health Informatics delivers a comprehensive overview of the most recent generative AI-driven medical applications based on deep learning and machine learning in which biomedical data is gathered, processed, and analyzed using data augmentation techniques. This book covers many applications of generative models for medical image data, including volumetric medical image segmentation, data augmentation, MRI reconstruction, and modeling of spatiotemporal medical data.
This book explores findings obtained by explainable AI techniques, with coverage of various techniques rarely reported in literature. Throughout the book, feedback and user experiences from physicians and medical staff, as well as use cases, are included to provide important context.
This book discusses topics including privacy and security challenges in AI-enabled health informatics, biosensor-guided AI interventions in personalized medicine, regulatory frameworks and guidelines for AI-based medical devices, education and training for building responsible AI solutions in healthcare, and challenges and opportunities in integrating generative AI with wearable devices.
Topics covered include:
Generative Artificial Intelligence for Biomedical and Smart Health Informatics is an essential reference on the subject for computer science researchers, medical professionals, healthcare informatics, and medical imaging researchers interested in understanding the potential of artificial intelligence and other related technologies in healthcare.
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Enables readers to understand the future of medical applications with generative AI and related applications
Generative Artificial Intelligence for Biomedical and Smart Health Informatics delivers a comprehensive overview of the most recent generative AI-driven medical applications based on deep learning and machine learning in which biomedical data is gathered, processed, and analyzed using data augmentation techniques. This book covers many applications of generative models for medical image data, including volumetric medical image segmentation, data augmentation, MRI reconstruction, and modeling of spatiotemporal medical data.
This book explores findings obtained by explainable AI techniques, with coverage of various techniques rarely reported in literature. Throughout the book, feedback and user experiences from physicians and medical staff, as well as use cases, are included to provide important context.
This book discusses topics including privacy and security challenges in AI-enabled health informatics, biosensor-guided AI interventions in personalized medicine, regulatory frameworks and guidelines for AI-based medical devices, education and training for building responsible AI solutions in healthcare, and challenges and opportunities in integrating generative AI with wearable devices.
Topics covered include:
Generative Artificial Intelligence for Biomedical and Smart Health Informatics is an essential reference on the subject for computer science researchers, medical professionals, healthcare informatics, and medical imaging researchers interested in understanding the potential of artificial intelligence and other related technologies in healthcare.
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