Kansal mrignainy (37 risultati)

Condizione: New. pp. 375.

Condizione: New. pp. 375.

Condizione: New. pp. 375.

Condizione: New.

Taschenbuch. Condizione: Neu. Neuware - Applications of Artificial Intelligence in Industry and Services explores the integration of machine learning, data analytics, intelligent automation, and emerging AI technologies within the context of Industry 4.0, demonstrating their transformative impact on operational efficiency, decision-making, and service innovation. The book is organized to guide readers from the fundamentals of artificial intelligence to advanced sector-specific applications. Initial chapters introduce core concepts and enabling technologies, including machine learning, deep learning, natural language processing, and computer vision. Subsequent chapters examine AI-driven solutions across diverse domains, including manufacturing, healthcare, finance, supply chain management, smart cities, and service operations. Emerging topics, including explainable AI, ethical and responsible AI practices, human-AI collaboration, and AI-enabled digital twins, are also explored through frameworks, case studies, and performance analyses. The book offers multidisciplinary perspectives and state-of-the-art methodologies to highlight the opportunities and challenges associated with deploying intelligent systems, while also offering practical insights into the design, implementation, and evaluation of scalable and responsible AI solutions. Key Features: -Discusses the role of AI technologies and their role in shaping Industry 4.0 with detailed discussions on machine learning, deep learning, natural language processing, and computer vision. -Covers emerging topics such as explainable AI, ethical AI, digital twins, and human-AI collaboration. Integration of real-world case studies, frameworks, and performance evaluations -Multidisciplinary perspectives combining theoretical concepts with practical deployment strategies and applications across manufacturing, healthcare, finance, supply chains, smart cities, and service management.…

Condizione: New.

Condizione: New.

Condizione: New.

Hardback. Condizione: New.

Condizione: New.

Hardback. Condizione: New.

Hardback. Condizione: New.

Hardback. Condizione: New.

Hardback. Condizione: New. The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harness these technologies effectively, enhancing software development, testing, maintenance, and deployment processes. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics. Moreover, the forward-looking section discussing future trends and research directions will inspire readers to explore new avenues in software engineering. This book serves as a valuable resource for those seeking to leverage advanced technologies to improve software engineering processes, making it an essential addition to the library of anyone involved in software development.…

Hardback. Condizione: New. The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. It equips readers with the knowledge and practical insights needed to harness these technologies effectively, enhancing software development, testing, maintenance, and deployment processes. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics. Moreover, the forward-looking section discussing future trends and research directions will inspire readers to explore new avenues in software engineering. This book serves as a valuable resource for those seeking to leverage advanced technologies to improve software engineering processes, making it an essential addition to the library of anyone involved in software development.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. Applications of Artificial Intelligence in Industry and Services explores the integration of machine learning, data analytics, intelligent automation, and emerging AI technologies within the context of Industry 4.0, demonstrating their transformative impact on operational efficiency, decision-making, and service innovation. The book is organized to guide readers from the fundamentals of artificial intelligence to advanced sector-specific applications. Initial chapters introduce core concepts and enabling technologies, including machine learning, deep learning, natural language processing, and computer vision. Subsequent chapters examine AI-driven solutions across diverse domains, including manufacturing, healthcare, finance, supply chain management, smart cities, and service operations. Emerging topics, including explainable AI, ethical and responsible AI practices, human-AI collaboration, and AI-enabled digital twins, are also explored through frameworks, case studies, and performance analyses. The book offers multidisciplinary perspectives and state-of-the-art methodologies to highlight the opportunities and challenges associated with deploying intelligent systems, while also offering practical insights into the design, implementation, and evaluation of scalable and responsible AI solutions. Key Features: -Discusses the role of AI technologies and their role in shaping Industry 4.0 with detailed discussions on machine learning, deep learning, natural language processing, and computer vision. -Covers emerging topics such as explainable AI, ethical AI, digital twins, and human-AI collaboration. Integration of real-world case studies, frameworks, and performance evaluations -Multidisciplinary perspectives combining theoretical concepts with practical deployment strategies and applications across manufacturing, healthcare, finance, supply chains, smart cities, and service management. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. The integration of medical large language models (LLMs) and AI in healthcare transforms how medical professionals diagnose conditions, manage patient care, and access clinical information. These advanced technologies may improve efficiency, enhance decision-making, and expand access to healthcare services through applications like virtual assistants, medical documentation, predictive analytics, and personalized treatment recommendations. However, the increasing use of AI in clinical settings also raises important concerns related to ethics, patient privacy, bias, accountability, and trust between healthcare providers and patients. Further examination may reveal the opportunities and challenges associated with AI-driven systems in medicine, emphasizing the need for responsible, transparent, and human-centered approaches to healthcare innovation. Medical LLMs and AI in Healthcare: Ethics, Trust, and Clinical Applications explores the application of medical LLMs and AI in healthcare to support clinical decision-making, patient care, medical documentation, and healthcare accessibility. It examines the ethical, legal, and social implications of AI in medicine, including issues of trust, bias, privacy, accountability, and the relationship between technology, healthcare professionals, and patients. This book covers topics such as medical technologies, radiology, and data science, and is a useful resource medical and healthcare professionals, engineers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. Large Language Models (LLMs) are increasingly being explored in clinical settings, where they promise to support tasks such as documentation, decision support, and patient communication. However, the integration of medical LLMs introduces significant clinical safety considerations, as errors, or inappropriate recommendations can have real-world consequences for patient care. Clinical safety assessment plays a critical role in evaluating whether these systems perform reliably and within acceptable risk boundaries across diverse clinical scenarios. This assessment requires different methods to test accuracy, bias, and failure modes, as well as alignment with clinical standards, regulatory expectations, and ethical principles, to ensure that medical LLMs augment. Medical LLMs for Clinical Safety Assessment provides a comprehensive overview of clinical safety evaluation frameworks for medical LLMs. It connects AI research with medical practice by providing evidence-based models. Covering topics such as LLMS, medical technologies, and clinical assessment, this book is an excellent resource for researchers, machine learning engineers, data scientists, health leaders, policy makers, academicians, and graduate students. 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. Condizione: new. Hardcover. The integration of medical large language models (LLMs) and AI in healthcare transforms how medical professionals diagnose conditions, manage patient care, and access clinical information. These advanced technologies may improve efficiency, enhance decision-making, and expand access to healthcare services through applications like virtual assistants, medical documentation, predictive analytics, and personalized treatment recommendations. However, the increasing use of AI in clinical settings also raises important concerns related to ethics, patient privacy, bias, accountability, and trust between healthcare providers and patients. Further examination may reveal the opportunities and challenges associated with AI-driven systems in medicine, emphasizing the need for responsible, transparent, and human-centered approaches to healthcare innovation. Medical LLMs and AI in Healthcare: Ethics, Trust, and Clinical Applications explores the application of medical LLMs and AI in healthcare to support clinical decision-making, patient care, medical documentation, and healthcare accessibility. It examines the ethical, legal, and social implications of AI in medicine, including issues of trust, bias, privacy, accountability, and the relationship between technology, healthcare professionals, and patients. This book covers topics such as medical technologies, radiology, and data science, and is a useful resource medical and healthcare professionals, engineers, academicians, researchers, and scientists. 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. Condizione: new. Hardcover. Large Language Models (LLMs) are increasingly being explored in clinical settings, where they promise to support tasks such as documentation, decision support, and patient communication. However, the integration of medical LLMs introduces significant clinical safety considerations, as errors, or inappropriate recommendations can have real-world consequences for patient care. Clinical safety assessment plays a critical role in evaluating whether these systems perform reliably and within acceptable risk boundaries across diverse clinical scenarios. This assessment requires different methods to test accuracy, bias, and failure modes, as well as alignment with clinical standards, regulatory expectations, and ethical principles, to ensure that medical LLMs augment. Medical LLMs for Clinical Safety Assessment provides a comprehensive overview of clinical safety evaluation frameworks for medical LLMs. It connects AI research with medical practice by providing evidence-based models. Covering topics such as LLMS, medical technologies, and clinical assessment, this book is an excellent resource for researchers, machine learning engineers, data scientists, health leaders, policy makers, academicians, and graduate students. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…