Leveraging Futuristic Machine Learning And Next Generational Security For E Governance
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Leveraging Futuristic Machine Learning and Next-Generational Security for e-Governance
In an era defined by rapid technological advancement and a pressing need for effective governance, the intersection of machine learning and cybersecurity has emerged as a pivotal area of exploration and innovation. E-governance serves as a vital framework for enhancing the delivery of public services, increasing governmental transparency, and fostering citizen engagement. However, as governments increasingly rely on digital infrastructures, they expose themselves to a myriad of cyber threats that can undermine public trust and security. The contemporary landscape of e-governance must not only adapt to the wave of new digital tools but also ensure the security and integrity of the data that underpins them. Leveraging Futuristic Machine Learning and Next-Generational Security for e-Governance brings together a comprehensive collection of insights and research from leading experts in the fields of artificial intelligence, cybersecurity, and public administration. The contributions to this volume encompass theoretical frameworks, case studies, and practical applications that showcase the transformative potential of integrating machine learning with next-generation security solutions. With this resource, researchers, practitioners, and academics can work toward a new age where e-governance thrives at the nexus of machine learning and cybersecurity.
Driving Socio-Economic Growth With AI and Blockchain
In an era of rapid technological advancement, artificial intelligence (AI) and blockchain emerge as powerful catalysts for driving socio-economic growth. These innovations reshape industries, streamline processes, and unlock new opportunities for economic development. AI enhances productivity and innovation across sectors like healthcare, finance, and education. Meanwhile, blockchain's decentralized and secure practices transform industries by ensuring transparency, reducing fraud, and enabling efficient transactions. Together, AI and blockchain have the potential to create a more equitable and successful society by fostering inclusive growth, driving job creation, and improving access to essential services. Further exploration into how these technologies are driving socio-economic progress may highlight their impact on global economies and the future of work. Driving Socio-Economic Growth With AI and Blockchain examines the applications of blockchain technology and AI as catalysts for social and economic development. It discusses the use of these technologies in reaching sustainable development goals (SDGs) and increasing global economic growth. This book covers topics such as data science, financial technology, and sociology, and is a useful resource for data scientists, economists, sociologists, computer engineers, academicians, and researchers.
Smart Healthcare, Clinical Diagnostics, and Bioprinting Solutions for Modern Medicine
The concept of smart healthcare is considerably optimistic thanks to the applications of artificial intelligence as well as augmented and virtual reality (AR/VR) which work in tandem to enhance better results and better delivery of care. The algorithm developed with the help of modern technology is aimed at analyzing and interpreting a significant volume of clinical healthcare data with the aim of enhancing diagnosis and practices. Additionally, 3-dimesional (3D) bioprinting is revolutionizing healthcare by fabricating biological tissues and organs for clinical regenerative medicine and surgical advances. Thus, personalized medicine can go a step further with providing clinical treatments that have specific doses and drugs combinations of the patients in need. Smart Healthcare, Clinical Diagnostics, and Bioprinting Solutions for Modern Medicine explores the revolution that smart healthcare is having on the improvement of management of hospitals through increased operational efficiency, adequate conformation of resources, and smooth patient flows. It advances processes that are utilized in clinical diagnosis with the aid of predictive modelling with best practices. Covering topics such as disease prediction, remote healthcare monitoring, and intelligent healthcare supply chains, this book is an excellent resource for policymakers, clinicians, information technologists, data scientists, biomedical engineers, professionals, researchers, scholars, academicians, and more.