River Publishers Series in Biotechnology and Medical Research – serie

A new information and communication technology (ICT) has been deployed in the battle against Parkinson’s disease, a neurodegenerative disorder that is both progressive and disabling with significant impact on quality of life. This book explains the experience following from the achieved results in the REMPARK project on Parkinson’s disease management up to the launch of a new medical product to the European market, STAT-ON™.The new medical device, STAT-ON™ is a real Holter for the motor symptoms associated to PD. It provides objective information about the severity and distribution of PD motor symptoms and their fluctuations in daily life, allowing for an unbiased and correct monitoring of the patient. This real-time remote monitoring solution gives additional information to neurologists, opening up new possibilities for more effective treatment, more accurate control in clinical trials, and for early detection of motor complications.The number of PD patients is continuously rising, adding complexity, especially in the management at the level of public health. It is an incurable disease, with a symptomatic treatment that tries to alleviate the associated symptoms through a correct adjustment of the medication. For this reason, it is also very important to be aware of changes in the manifestation of the symptoms, which may indicate the need for an adjustment or even a change in the therapy strategy.The intensive complementary use of STAT-ON™ by neurologists, health professionals and researchers, will increase the independence and quality of life of patients, improving their disease management, and contributing to a deeper understanding of the nature of the disease.The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons [Attribution-Non-Commercial (CC-BY-NC)] 4.0 license.

In this book, we embark on a journey into the realm of predictive data modeling for biomedical data and imaging in healthcare. It explores the potential of predictive analytics in the field of medical science through utilizing various tools and techniques to unravel insights and enhance patient care. This volume creates a medium for an interchange of knowledge from expertise and concerns in the field of predictive data modeling. In detail, the research work on this will include the effective use of predictive data modeling algorithms to run image analysis tasks for understanding.Predictive Data Modelling for Biomedical Data and Imaging is divided into three sections, namely Section I – Beginning of Predictive Data Modeling for Biomedical Data and Imaging/Healthcare, Section II – Data Design and Analysis for Biomedical Data and Imaging/Healthcare, and Section III – Case Studies of Predictive Analytics for Biomedical Data and Imaging/Healthcare. We hope this book will inspire further research and innovation in the field of predictive data modeling for biomedical data and imaging in healthcare. By exploring diverse case studies and methodologies, this book contributes to the advancement of healthcare practices, ultimately improving patient outcomes and well-being.

Brain Tumors and Nanotechnology explores the complex world of brain tumors and the ground-breaking role that nanotechnology is playing in both detection and treatment. It offers comprehensive and up-to-date strategies in the treatment of brain tumors, with a special emphasis on the revolutionary impact of nanotechnology. It begins with an in-depth analysis of the anatomy of the brain and nervous system, highlighting the constituents of the central nervous system (CNS) such as neurons and glial cells. It also offers a thorough understanding of the intricate structure of the human brain, including the hemispheres, brainstem, diencephalon, and ventricular system. It then reveals the understanding of the complicated nature of brain tumors and the potential for nanotechnology to revolutionize their diagnosis and treatment. Brain Tumors and Nanotechnology will be a longstanding valuable resource for researchers, medical professionals, and students in the field.

This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT scans, MRIs, ultrasounds, etc.) to get images of the interior organs of a human being for potential diagnostic, treatment planning, follow-up, and surgical purposes. In these circumstances, deep learning, a new learning method that uses multi-layered artificial neural networks (ANNs) for unsupervised, supervised, and semi-supervised learning, has attracted a lot of interest for applications to NGS and imaging, even when both of these data are used for the same group of patients.The three main research phenomena in biomedical research are disease classification, feature dimension reduction, and heterogeneity. AI approaches are used by clinical researchers to efficiently analyse extremely complicated biomedical datasets (e.g., multi-omic datasets. With the use of NGS data and biomedical imaging of various human organs, researchers may predict diseases using a variety of deep learning models. Unparalleled prospects to improve the work of radiologists, clinicians, and biomedical researchers, speed up disease detection and diagnosis, reduce treatment costs, and improve public health are presented by using deep learning models in disease prediction using NGS and biomedical imaging. This book influences a variety of critical disease data and medical images.

This book provides in-depth information about the latest trends in transformer insulation design. This practical guide is prepared from a hands-on perspective, offering readers valuable insights into the trends in liquid dielectrics for transformer applications. Chapter 1 covers the necessity of alternate liquid dielectrics for transformers. Chapter 2 delves into the historical development of liquid dielectrics for transformer applications, drawing insights from reputable publications. It also explores the impact of nanoparticles on ester oil characteristics. In Chapter 3, the significance of spectroscopy analysis for investigating the ageing effect on both cellulosic insulating materials and oil samples is discussed. Chapter 4 describes material preparations followed by experimental analysis, estimating the degradation rate of solid and liquid dielectrics using spectroscopies. Chapter 5 discusses the importance of condition monitoring for transformers and its historical methods. Chapter 6 explores the methodology for hot spot indication and its application for assessing the transformer's condition. It covers real-time case studies as well. In Chapter 7, the book investigates the application of artificial intelligence in transformer insulation systems, leveraging machine learning algorithms to predict transformer insulation.

Decision Support System for Diabetes Healthcare: Advancements and Applications is a comprehensive guide to the cutting-edge technology transforming diabetes management. In this book, leading experts in the field explore how decision support systems (DSS) are revolutionizing healthcare practices, particularly in diabetes care. From advanced data analytics to personalized treatment recommendations, this book delves into the innovative solutions that are reshaping how healthcare providers approach diabetes management. Readers will gain insights into the latest developments in DSS technology, including predictive modeling, machine learning algorithms, and real-time monitoring systems, all designed to enhance patient outcomes and improve quality of life. With a focus on practical applications, Decision Support System for Diabetes Healthcare offers case studies and examples of successful DSS implementations across various healthcare settings. Whether you're a healthcare professional, researcher, or technology enthusiast, this book provides invaluable insights into the future of diabetes care. By exploring the intersection of technology and healthcare, readers will discover how DSS is empowering both patients and providers to make informed decisions, optimize treatment plans, and ultimately, transform the way diabetes is managed on a global scale.

This book is an in-depth exploration of brain networks, providing a comprehensive understanding of their structures, functions, and implications for personalization through artificial intelligence. Readers will gain insights into the intricate workings of the brain, making this book an indispensable resource for those seeking a thorough grasp of neuroscience concepts. It offers the seamless integration of neuroscience principles with artificial intelligence applications. The book bridges these two domains, elucidating how advancements in AI draw inspiration from the complexities of the human brain. This interdisciplinary approach sets the book apart, offering readers a holistic view of cutting-edge technologies. Readers can expect practical applications and real-world case studies that illustrate the tangible benefits of the concepts discussed. From personalized healthcare solutions to adaptive learning systems, the book goes beyond theory, empowering readers to apply knowledge in diverse domains. This practical emphasis enhances the book’s relevance for professionals and researchers alike. The inclusion of online enhancements, such as interactive visualizations, downloadable supplementary materials, and engaging video content, transforms the reading experience into an interactive learning journey. This added value distinguishes the book by providing readers with hands-on tools to deepen their understanding and apply newfound knowledge.This book doesn’t just dwell on current technologies; it takes readers into the future by exploring emerging trends at the intersection of neuroscience and artificial intelligence. By delving into potential breakthroughs and innovations, the book equips readers with insights that are forward-thinking and relevant in an ever-evolving technological landscape.

The pharmaceutical industry is on the cusp of a new age, with the need for personalized therapy, more complex production processes, smaller batch sizes and rising manufacturing costs. It is necessary to continuously adapt to the rapidly changing environment using novel technology and improved operational efficiency and flexibility. To achieve this, intelligent manufacturing seems to be a definite answer. Pharma 4.0 is a framework for adapting digital strategies to the unique contexts of pharmaceutical manufacturing. This book provides a deep insight into key technologies that will modernize pharmaceutical manufacturing and facilitate digital transformation. Throughout the book we discuss technologies, application and challenges for applying digital technology in pharmaceutical industry, including: • Focus on an overview of Industry 4.0 and its application in the pharmaceutical field• Most recent advances in the pharmaceutical industry• Understanding the concepts of emerging technology trends for drug discovery.

This book examines recent key findings on the mechanisms of axonal and dendritic remodeling in different model organisms. Each chapter is contributed by a panel of experts in their respective subfields of neurosciences, to provide and discuss the latest discoveries ranging from neuronal morphogenesis during development, experience-dependent structural plasticity, to neuronal degeneration, regeneration, and pathologies in neurological disorders.The process of neuronal remodeling, specifically their axons and dendrites, is essential for the proper wiring of the nervous system during early development and continues during postnatal ages to shape the pattern of synaptic connections throughout the life of the organism, including humans. Over recent years, substantial progress has been made in our understanding of the cellular and molecular mechanisms that control neuronal remodeling. In addition, there is accumulating evidence demonstrating how the nervous system could remodel in response to injury and in pathological conditions.Topics discussed in the book include:Axonal degeneration during development and in pathological or disease conditionsNeuronal morphogenesis (axons and dendrites)Experience-dependent structural plasticity to synaptogenesisDendrite degeneration and regeneration