Mathematical Methods in the Digital Age – serie

The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.

The book presents powerful optimization approaches for integrating AI into daily life.This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.

The book is likely intended to provide a thorough knowledge of the complex relationships between computational intelligence, mathematical computing, and sustainability. By taking an interdisciplinary approach, the author may strive to connect theoretical frameworks with practical applications, providing readers with a road map for navigating the intricacies of addressing long-term difficulties. The book could use case studies and examples to demonstrate how cutting-edge technologies and mathematical models can be used to analyse and solve real-world sustainability problems, ultimately encouraging a holistic approach that fosters innovative solutions based on computational and mathematical principles. This book is planned to cover the comprehensive investigation into the synergies between Computational Intelligence (CI), Mathematical Computing, and Sustainability. An examination of the possible impact of intelligent systems on sustainability, new concepts and approaches for incorporating CI and mathematical computing into sustainable practices etc. There will be chapters explaining the Exploration of upcoming technologies (e.g., quantum computing, bio-inspired computing) and their potential role in promoting sustainability.

This book is intended for a technical audience with advanced learning and in-depth analysis of the latest real-world developments in the field of quantum computing. The book is focused on modeling emerging drone-based applications. The methods of developing faster drive with the new trending technology of quantum genetic heuristics, artificial intelligence, and machine-based applications are discussed. Researchers will find novel ways to secure the data and Quantum drone networks. The book examines the most promising exploratory quantum-computed drone that optimizes, secures, and dynamically analyses various sectors, including healthcare, the educational industry, finance, transportation, and manufacturing.

This book offers a comprehensive and interdisciplinary perspective on healthcare intelligent systems, highlighting the growing role of applied mathematics, data-driven methodologies, and artificial intelligence in modern healthcare. The book brings together scholarly contributions that explore how intelligent models, data representations, and computational techniques are applied to healthcare diagnostics, medical imaging, and clinical decision-support systems.The chapters cover a wide range of topics, including medical imaging modalities, data handling and representation, deep learning techniques, explainable and trustworthy artificial intelligence, generative models, three-dimensional reconstruction, performance evaluation metrics, ethical considerations, and emerging trends in healthcare technologies. Through practical insights and real-world case studies, the volume illustrates how intelligent systems support disease detection, diagnosis, and personalized treatment planning.Designed for researchers, graduate students, and professionals in healthcare technology, computer science, and biomedical engineering, this book serves as a valuable reference on intelligent healthcare solutions.

The book explores the mathematical and computational techniques used in Decentralized Finance (DeFi) and Financial Technology (FinTech).DeFi operates on smart contracts, which are self-executing programs that automate the necessary actions for conducting transactions on a blockchain.FinTech encompasses a broader range of services, including digital payments, mobile banking, and financial analytics, often powered by machine learning and data science.This book integrates mathematical concepts such as cryptographic algorithms, stochastic modeling, optimization, and game theory with computer science principles of Consensus mechanisms in cryptocurrency networks that include:Proof-of-Work (PoW): Users solve complex computational puzzles to add new blocks to the blockchain.Proof-of-Stake (PoS): Users validate transactions based on the number of coins they hold and are willing to 'stake' for network security.The aim is to use such a combination to enhance the security, stability, and efficiency of automated systems for decentralized exchanges, lending protocols, and automated markets. Furthermore, advancements in computation—such as artificial intelligence, big data, and cloud computing—improve DeFi by enabling the prediction of asset movements, analyzing user behavior, and supporting scalable decentralized applications. Despite rapid advancements, challenges remain, particularly in areas like smart contract vulnerabilities, market volatility, and regulatory compliance. Ongoing interdisciplinary research is focused on addressing these issues through improved composability and integration of mathematics with computation. These innovations promote global participation, transparency, and financial inclusion.

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.

Data science, quantitative analysis, computer optimisation, and machine learning are all explored in this book. Insightful mathematical analysis of ML models is presented in this work. Various fields, including healthcare, banking, and e-commerce, are covered in this book through case studies. To choose features, hyperparameters, and models, the latter shows how optimisation can be implemented. Practical insights on the assessment and improvement of machine learning models in real-world situations, such as e-commerce, healthcare, banking, and agriculture, are included. Professionals in the fields of research, engineering, mathematics, and computer science are the target audience for this book. Through the integration of theoretical principles with practical applications, the usage of computational optimisation techniques in real-time settings is to be enhanced.

The book was inspired by the urgent need for advanced security methods that can keep pace with the increasingly complex nature of modern healthcare systems. In the age of medical networks, incorporating fuzzy logic provides a flexible, adaptive approach to security, enhancing traditional methods of safeguarding patient data, medical devices, and sensitive health records. It presents fuzzy logic as a tool for providing dynamic, intelligent security solutions, exploring its application in risk assessment, anomaly detection, and real-time decision-making processes. By addressing both theoretical frameworks and practical implementations, the book offers comprehensive strategies for establishing resilient, secure healthcare environments. Ultimately, the book is essential reading for healthcare professionals, IT specialists and researchers, and healthcare industries. It provides them with the knowledge to fortify next-generation healthcare systems against cyber threats, ensuring safety and confidence in digital health innovations.

This book explores advanced mathematical computational algorithms in artificial intelligence and robotics, with a focus on areas such as machine learning, optimization, and digital simulations. Key topics include the mathematical foundations of AI, robotics control systems, computational geometry for image processing, and their applications in real-world problem-solving, such as autonomous systems and smart manufacturing.