Generative Artificial Intelligence Biomedical (22 results)

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- Hardcover
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Buch. Condition: Neu. Neuware - The Internet of Medical Things (IoMT) paradigm focuses on digitizing medical electronics and instruments in hospital environments, connecting them to cloud-hosted healthcare-related content, data, services, and applications through the Internet communication infrastructure. This book also illustrates how such a technological empowerment makes healthcare devices and equipment intelligently autonomous in their decisions, actions, and reactions. It elucidates the latest trends and transitions in the field of IoMT for medical doctors, surgeons, specialists, caregivers, and patients. It covers algorithms used in machine learning, deep learning, reinforcement learning and ensemble learning, as well as the individual steps involved in AI model development, and explains how to analyse healthcare data effectively. Additionally, generative AI tools -including large, small, vision, and multimodal language models -are useful for envisioning and implementing expert decision science, question/answer (Q/A) systems, and conversational AI chatbots to support medical professionals in their work. This book is a handholding guide for healthcare service providers and consumers, AI engineers, 5G, edge computing and IoT architects.…

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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 304 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Hardcover. Condition: new. Hardcover. 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. The book explores findings obtained by explainable AI techniques, with coverage of various techniques rarely reported in literature. Throughout, feedback and user experiences from physicians and medical staff, as well as use cases, are included to provide important context. The 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: Treatment of neurological disorders using intelligent techniques and image-guided and tomography interventions for neuromuscular disordersBio-inspired smart healthcare service frameworks with AI, machine learning, and deep learning, integration of IoT devices, and edge computing in industrial and clinical systemsTraffic management and optimization in distributed environments, patient data management, disease surveillance and prediction, and telemedicine and remote monitoringEducation-driven, peer-to-peer, and service-oriented architectures and transparency and accountability in medical decision-making Generative Artificial Intelligence for Biomedical and Smart Health Informatics is an essential reference 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

- Hardcover
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Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 704 pages. 6.00x1.50x9.00 inches. In Stock. This item is printed on demand.