Sushruta Mishra – författare

Cognitive Big Data Intelligence with a�Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity.

This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.

Provides a unique opportunity to present the work on the state-of-the-art of metaheuristics approach in the area of big data processing developing automated and intelligent models Explains different, feasible applications and case studies where cognitive computing can be successfully implemented in big data analytics using metaheuristics algorithms Provides a snapshot of the latest advances in the contribution of metaheuristics frameworks in cognitive big data applications to solve optimization problems

This book aims to apply state-of-the-art advanced computational intelligence frameworks in healthcare. It presents recent and real-life applications of computationally intelligent healthcare. It also discusses problems and solutions to remote healthcare and emergency healthcare services. Healthcare Analytics and Advanced Computational Intelligence highlights modern ambient intelligence-enabled healthcare models along with advanced topics like quantum computing in healthcare and cryptomedical systems.Healthcare Analytics and Advanced Computational Intelligence examines designing the latest medical systems and models that will allow the societal acceptance of ambiance computing in healthcare, medical imaging, health analytics, machine intelligence, sensory computing, medical data analytics, disease detection, telemedicine, and their applications. It includes diverse case studies dealing with various clinical-based applications. These intelligent models are primarily structured to deal with complex real-world issues in clinical data analytics, by means of state-of-the-art techniques with general implementation, domain-specific solutions, or hybrid methods which integrate computational intelligence with conventional statistical methods.The book is written for researchers and academicians in diverse areas. Engineers from technical disciplines such as computer engineering are likely to purchase the book. Various sub-streams such as machine learning, big data analytics, healthcare analytics, and computational intelligence will find the book significant for their curriculum.

This book aims to apply state-of-the-art advanced computational intelligence frameworks in healthcare. It presents recent and real-life applications of computationally intelligent healthcare. It also discusses problems and solutions to remote healthcare and emergency healthcare services. Healthcare Analytics and Advanced Computational Intelligence highlights modern ambient intelligence-enabled healthcare models along with advanced topics like quantum computing in healthcare and cryptomedical systems.Healthcare Analytics and Advanced Computational Intelligence examines designing the latest medical systems and models that will allow the societal acceptance of ambiance computing in healthcare, medical imaging, health analytics, machine intelligence, sensory computing, medical data analytics, disease detection, telemedicine, and their applications. It includes diverse case studies dealing with various clinical-based applications. These intelligent models are primarily structured to deal with complex real-world issues in clinical data analytics, by means of state-of-the-art techniques with general implementation, domain-specific solutions, or hybrid methods which integrate computational intelligence with conventional statistical methods.The book is written for researchers and academicians in diverse areas. Engineers from technical disciplines such as computer engineering are likely to purchase the book. Various sub-streams such as machine learning, big data analytics, healthcare analytics, and computational intelligence will find the book significant for their curriculum.

This book covers a wide range of advanced techniques and approaches for designing and implementing computationally intelligent methods in different application domains which is of great use to not only researchers but also academicians and industry experts. Optimized Computational Intelligence (OCI) is a new, cutting-edge, and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, biologically-inspired computation, software engineering, AI, cybernetics, cognitive science, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences. OCI aims to apply modern computationally intelligent methods to generate optimum outcomes in various application domains. This book presents the latest technologies-driven material to explore optimized various computational intelligence domains. includes real-life case studies highlighting different advanced technologies in computational intelligence;provides a unique compendium of current and emerging hybrid intelligence paradigms for advanced informatics;reflects the diversity, complexity, and depth and breadth of this critical bio-inspired domain;offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in dealing with cognitive informatics challenges;presents a variety of intelligent and optimized techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional data analytics research in intelligent decision-making system dynamics;includes architectural models and applications-based augmented solutions for optimized computational intelligence.Audience The book will interest a range of engineers and researchers in information technology, computer science, and artificial intelligence working in the interdisciplinary field of computational intelligence.

Equip yourself with the multidisciplinary expertise to lead the digital medicine revolution with this comprehensive guide to the cutting-edge intersection of wearable technology, data science, and clinical care.The rapid evolution of digital technology has transformed nearly every aspect of human life from communication and entertainment to healthcare and medicine. Among these advancements, smart wearables have emerged as a vital element of modern digital medicine, redefining how we monitor, diagnose, and manage health conditions. This book explores the dynamic intersection of wearable technology and medical science, providing an in-depth understanding of how these devices are revolutionizing healthcare delivery, patient monitoring, and disease management. By bridging engineering, data science, and clinical applications, it serves as a comprehensive resource for researchers, healthcare professionals, technology developers, and students interested in digital medicine.Readers will find the volume: Emphasizes the importance of wearable-enabled e-medicine to create a smart and intelligent healthcare network;Introduces advanced architectural frameworks of digital healthcare and clinical systems;Provides diversified applications and case studies on smart wearable-enabled personalized healthcare services;Explores futuristic enhancements and challenges of different technologies in the context of wearable computing supported by e-medicine;Highlights techniques and methodologies related to emergency healthcare and improved customized patient care.AudienceAcademics, engineers, medical professionals, research scientists, hospital administrators, and industry professionals looking to innovate the future of personalized healthcare.

With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere.

With rise of smart medical sensors, cloud computing and the health care technologies, “connected health” is getting remarkable consideration everywhere. Recently, the Internet of Things (IoT) has brought the vision of a smarter world into reality. Cloud computing fits well in this scenario as it can provide high quality of clinical experience. Thus an IoT-cloud convergence can play a vital role in healthcare by offering better insight of heterogeneous healthcare content supporting quality care. It can also support powerful processing and storage facilities of huge data to provide automated decision making. This book aims to report quality research on recent advances towards IoT-Cloud convergence for smart healthcare, more specifically to the state-of-the-art approaches, design, development and innovative use of those convergence methods for providing insights into healthcare service demands. Students, researchers, and medical experts in the field of information technology, medicine, cloud computing, soft computing technologies, IoT and the related fields can benefit from this handbook in handling real-time challenges in healthcare. Current books are limited to focus either on soft computing algorithms or smart healthcare. Integration of smart and cloud computing models in healthcare resulting in connected health is explored in detail in this book.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies.

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies.

The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.

The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.

This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare.