AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.Includes case studies and real-world applications to illustrate the effectiveness of intelligent cybersecurity solutionsDiscusses the increasing integration of artificial intelligence (AI) in healthcare systems, highlighting its role in enhancing medical diagnosis, treatment planning, and patient careFocuses on advanced techniques for enhancing data security while maintaining patient privacy

Self-Learning AI in Healthcare: Agentic Systems for Smarter Medicine covers the transformative potential of advanced artificial intelligence within modern medicine. The book addresses the critical need for self-learning and agentic AI systems that autonomously adapt, refine decision-making, and navigate complex clinical environments with minimal intervention. Chapters provide foundational insights into the rise of self-learning AI and neural networks tailored for adaptive medical systems. Subsequent chapters delve into unsupervised, semi-supervised, and reinforcement learning for autonomous healthcare decision-making, alongside decentralized edge AI approaches. Specialized sections cover personalized medicine, hospital workflow optimization, remote patient monitoring, early disease detection, federated learning for privacy preservation, and more.Further, this book explores AI applications in drug discovery, mental health support, radiology, digital twins, and medical robotics, culminating with an examination of future challenges, ethics, and regulatory frameworks shaping self-learning AI’s trajectory in healthcare. It is tailored to serve a diverse yet specialized audience spanning academic, professional, and research sectors. Healthcare IT professionals and clinical informatics specialists will gain practical guidance for implementing adaptive AI solutions within complex healthcare environments. AI researchers and data scientists focused on developing self-learning models will find cutting-edge methodologies and case studies that advance medical applications.Enhances understanding of autonomous AI systems for improved diagnostic accuracy and personalized treatment optimization in healthcareProvides practical insights into integrating adaptive AI for streamlined hospital workflows and real-time patient monitoringAddresses ethical, regulatory, and privacy challenges critical to deploying AI in sensitive medical environmentsOffers interdisciplinary perspectives that benefit students, researchers, and healthcare professionals seeking advanced AI applicationsExplores cutting-edge AI techniques for accelerating drug discovery, rehabilitation, and autonomous medical robotics

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.

Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives Critically analyzes contemporary challenges with practical strategies for addressing issues effectively Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management

This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.

Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives Critically analyzes contemporary challenges with practical strategies for addressing issues effectively Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management

This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performancePresents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologiesExamines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiativesCritically analyzes contemporary challenges with practical strategies for addressing issues effectivelyRecommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green managementThis reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

"Smart Forestry 5.0 for Powered AI Sustainable Environment and Climate" explores the transformative potential of integrating advanced artificial intelligence (AI) technologies into forestry practices. This book delves into how the fifth industrial revolution can reshape the way we manage forests, promoting sustainability and resilience in the face of climate change. It combines theoretical insights with practical applications, providing a comprehensive guide for researchers, practitioners, and policymakers.The book is structured around several key themes which includes Foundations of Smart Forestry, AI and Data-Driven Decision Making, Innovative Applications of AI, Ecosystem Monitoring and Restoration, Collaborative Frameworks for Sustainable Practices, Ethical Considerations in Smart Forestry, Future Trends and Innovations that highlight the intersection of smart forestry and AI, emphasizing sustainability in forest management. It discusses innovative technologies and methodologies that enable efficient monitoring, management, and restoration of forest ecosystems.

AI-Driven Cybersecurity for Intelligent Healthcare Systems explores the intersection between AI, cybersecurity, and healthcare. The book offers detailed insights into the unique cybersecurity challenges faced by the healthcare sector and the role of AI in addressing these challenges. It presents case studies and real-world applications to illustrate the effectiveness of these solutions and highlights the significance of data privacy in healthcare and methods to ensure secure data sharing and storage. Topics such as federated learning, homomorphic encryption, and blockchain technology are covered to demonstrate how AI can enhance data security without compromising patient privacy.This book will be an essential resource for anyone involved in the healthcare industry, offering practical solutions and fostering a more in-depth understanding of how AI can revolutionize cybersecurity in healthcare.Includes case studies and real-world applications to illustrate the effectiveness of intelligent cybersecurity solutionsDiscusses the increasing integration of artificial intelligence (AI) in healthcare systems, highlighting its role in enhancing medical diagnosis, treatment planning, and patient careFocuses on advanced techniques for enhancing data security while maintaining patient privacy

Self-Learning AI in Healthcare: Agentic Systems for Smarter Medicine covers the transformative potential of advanced artificial intelligence within modern medicine. The book addresses the critical need for self-learning and agentic AI systems that autonomously adapt, refine decision-making, and navigate complex clinical environments with minimal intervention. Chapters provide foundational insights into the rise of self-learning AI and neural networks tailored for adaptive medical systems. Subsequent chapters delve into unsupervised, semi-supervised, and reinforcement learning for autonomous healthcare decision-making, alongside decentralized edge AI approaches. Specialized sections cover personalized medicine, hospital workflow optimization, remote patient monitoring, early disease detection, federated learning for privacy preservation, and more.Further, this book explores AI applications in drug discovery, mental health support, radiology, digital twins, and medical robotics, culminating with an examination of future challenges, ethics, and regulatory frameworks shaping self-learning AI’s trajectory in healthcare. It is tailored to serve a diverse yet specialized audience spanning academic, professional, and research sectors. Healthcare IT professionals and clinical informatics specialists will gain practical guidance for implementing adaptive AI solutions within complex healthcare environments. AI researchers and data scientists focused on developing self-learning models will find cutting-edge methodologies and case studies that advance medical applications.Enhances understanding of autonomous AI systems for improved diagnostic accuracy and personalized treatment optimization in healthcareProvides practical insights into integrating adaptive AI for streamlined hospital workflows and real-time patient monitoringAddresses ethical, regulatory, and privacy challenges critical to deploying AI in sensitive medical environmentsOffers interdisciplinary perspectives that benefit students, researchers, and healthcare professionals seeking advanced AI applicationsExplores cutting-edge AI techniques for accelerating drug discovery, rehabilitation, and autonomous medical robotics

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.

Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives Critically analyzes contemporary challenges with practical strategies for addressing issues effectively Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management

This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.

Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performance Presents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologies Examines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiatives Critically analyzes contemporary challenges with practical strategies for addressing issues effectively Recommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green management

This reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

This book offers a detailed examination of how sustainable technologies are reshaping firm performance. Through an integration of empirical research, expert opinions, and case studies, it explores how green management practices are enhancing business outcomes and contributing to sustainable development. It offers an in-depth understanding of how green technologies and practices, such as green engineering, AI/ML applications, green HRM, and green innovation, impact firm performance.Explores topics such as green engineering, AI/ML applications, green finance, green HRM, and green innovation, showing their collective impact on business performancePresents real-world case studies and empirical findings to demonstrate how organizations across different industries have successfully implemented sustainable technologiesExamines regional variations in green management practices, offering insights into the impact of economic, regulatory, and cultural contexts on sustainability initiativesCritically analyzes contemporary challenges with practical strategies for addressing issues effectivelyRecommends actionable policy and future research directions for sustainable business practices, providing a roadmap for advancing green managementThis reference book is for academicians, scholars, and practitioners who are interested in emerging technologies that are reshaping firm performance and impacting sustainability.

"Smart Forestry 5.0 for Powered AI Sustainable Environment and Climate" explores the transformative potential of integrating advanced artificial intelligence (AI) technologies into forestry practices. This book delves into how the fifth industrial revolution can reshape the way we manage forests, promoting sustainability and resilience in the face of climate change. It combines theoretical insights with practical applications, providing a comprehensive guide for researchers, practitioners, and policymakers.The book is structured around several key themes which includes Foundations of Smart Forestry, AI and Data-Driven Decision Making, Innovative Applications of AI, Ecosystem Monitoring and Restoration, Collaborative Frameworks for Sustainable Practices, Ethical Considerations in Smart Forestry, Future Trends and Innovations that highlight the intersection of smart forestry and AI, emphasizing sustainability in forest management. It discusses innovative technologies and methodologies that enable efficient monitoring, management, and restoration of forest ecosystems.