Vidyapati Kumar – författare

Biomedical Robots and Devices in Healthcare: Opportunities and Challenges for Future Applications explores recent advances and challenges involved in using these techniques in healthcare and biomedical engineering, offering insights and guidance to researchers, professionals, and graduate students interested in this area. The book covers key topics such as the current state-of-the-art in biomedical robotics and devices, the role of emerging technologies like artificial intelligence and machine learning, rehabilitation robotics, and the optimization techniques for optimal design and control. The book concludes by exploring the potential future developments and trends in the field of biomedical robotics and devices and their healthcare implications.Provides a comprehensive overview of the current state-of-the-art in biomedical robotics and devices, including a discussion of the various types of devices and robots that are being developed and used in healthcare settingsHighlights the role of computational intelligence techniques such as artificial intelligence, machine learning, Fuzzy Logic, and evolutionary algorithms in the design, development, and the use of biomedical robots and devices, offering insights and guidance to professionals and students on these technologiesExplores the potential future developments and trends in the field of biomedical robotics and devices and their implications for healthcare professionals and patients, providing a valuable resource for those looking to stay up-to-date on advancements in the field

Biomedical Robots and Devices in Healthcare: Opportunities and Challenges for Future Applications explores recent advances and challenges involved in using these techniques in healthcare and biomedical engineering, offering insights and guidance to researchers, professionals, and graduate students interested in this area. The book covers key topics such as the current state-of-the-art in biomedical robotics and devices, the role of emerging technologies like artificial intelligence and machine learning, rehabilitation robotics, and the optimization techniques for optimal design and control. The book concludes by exploring the potential future developments and trends in the field of biomedical robotics and devices and their healthcare implications.- Provides a comprehensive overview of the current state-of-the-art in biomedical robotics and devices, including a discussion of the various types of devices and robots that are being developed and used in healthcare settings- Highlights the role of computational intelligence techniques such as artificial intelligence, machine learning, Fuzzy Logic, and evolutionary algorithms in the design, development, and the use of biomedical robots and devices, offering insights and guidance to professionals and students on these technologies- Explores the potential future developments and trends in the field of biomedical robotics and devices and their implications for healthcare professionals and patients, providing a valuable resource for those looking to stay up-to-date on advancements in the field

Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics demonstrates real-world applications of decision intelligence - specifically machine learning, robotics, and analytics - to drive innovation and improvements in healthcare delivery and outcomes. The book provides a comprehensive overview of the latest developments in decision intelligence technologies, and offers a practical resource that can help navigate through the complex landscape of healthcare decision-making. In 5 themes Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics focuses on the use of data analytics aad management techniques in healthcare to improve decision-making and healthcare outcomes, on the use of robotics, robots and genomics to improve biomedical informatics, on the use of genomics, clinical decision support systems (CDSS), machine learning, and deep learning to improve precision medicine and personalized treatment and on the ethical implications of using artificial intelligence (AI) in healthcare, ensuring trust in the technology, and making sure that it can be explained and understood by all stakeholders. This book is a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.Provide up-to-date knowledge on decision intelligence technologies, such as machine learning, robotics, and data analytics their applications in the field of healthcarePresents a range of case studies, practical examples, and theoretical concepts that illustrate how decision intelligence can be applied in areas such as diagnosis, treatment planning, and resource allocationEmpowers readers to make informed decisions that can improve the quality of care and outcomes for patients, while also enhancing the efficiency and effectiveness of healthcare systems

Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics demonstrates real-world applications of decision intelligence - specifically machine learning, robotics, and analytics - to drive innovation and improvements in healthcare delivery and outcomes. The book provides a comprehensive overview of the latest developments in decision intelligence technologies, and offers a practical resource that can help navigate through the complex landscape of healthcare decision-making. In 5 themes Advancing Healthcare through Decision Intelligence: Machine Learning, Robotics, and Analytics in Biomedical Informatics focuses on the use of data analytics aad management techniques in healthcare to improve decision-making and healthcare outcomes, on the use of robotics, robots and genomics to improve biomedical informatics, on the use of genomics, clinical decision support systems (CDSS), machine learning, and deep learning to improve precision medicine and personalized treatment and on the ethical implications of using artificial intelligence (AI) in healthcare, ensuring trust in the technology, and making sure that it can be explained and understood by all stakeholders. This book is a valuable resource for health professionals, scientists and researchers, health practitioners, students, and all those who wish to broaden their knowledge in the allied field.- Provide up-to-date knowledge on decision intelligence technologies, such as machine learning, robotics, and data analytics their applications in the field of healthcare- Presents a range of case studies, practical examples, and theoretical concepts that illustrate how decision intelligence can be applied in areas such as diagnosis, treatment planning, and resource allocation- Empowers readers to make informed decisions that can improve the quality of care and outcomes for patients, while also enhancing the efficiency and effectiveness of healthcare systems

This book examines the fundamentals of quantum computing and its applications in codebreaking and hacking, as well as strategies and technologies for defending systems against quantum attacks. It brings together leading experts from across academia and industry to provide a comprehensive overview of the impacts of quantum computing on cybersecurity and cryptography. As quantum computers become more powerful and practical in the coming years, they pose a serious threat to current encryption and cybersecurity methods which rely on computational difficulty. The book provides readers with a holistic understanding of the quantum computing landscape and its implications on information security.The chapters cover the foundational concepts of quantum mechanics and key quantum algorithms relevant to cryptography and cybersecurity. Detailed discussions on quantum cryptanalysis, post-quantum cryptography, quantum key distribution, and quantum random number generation equip readers with technical knowledge of quantum-safe cryptosystems. Practical topics such as quantum programming, software tools, and implementation of quantum-resistant solutions in different sectors like finance, healthcare, and the Internet of Things provide actionable insights for organizations. The book concludes with an analysis of collaborative strategies, policies and future research directions to foster innovation in quantum-safe cybersecurity. Overall, this book serves as an essential reference for security professionals, researchers, students, and technology leaders interested in preparing systems and data for the quantum computing era.