Indranath Chatterjee – författare

Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals.The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery. This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.

Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications focuses on automated analytical techniques for healthcare applications used to extract knowledge from a vast amount of data. It brings together a variety of different aspects of the healthcare system and aids in the decision-making processes for healthcare professionals.The editors connect four contemporary areas of research rarely brought together in one book: artificial intelligence, big data analytics, knowledge modelling, and healthcare. They present state-of-the-art research from the healthcare sector, including research on medical imaging, healthcare analysis, and the applications of artificial intelligence in drug discovery. This book is intended for data scientists, academicians, and industry professionals in the healthcare sector.

The Neuroscience of Coffee is a pioneering volume that delves into the intricate relationship between one of the world's most beloved beverages and the human brain. Offering a comprehensive exploration of the biochemical and physiological mechanisms underlying coffee's impact on the nervous system, this groundbreaking book transcends traditional coffee literature by focusing specifically on the neurological aspects. From deciphering the molecular intricacies of caffeine to examining the complex interactions within the nervous system, the volume provides an unprecedented insight into how coffee influences brain function, mental health, and neurodegenerative diseases. It addresses the growing interest in understanding everyday dietary choices and their neurological implications, filling a crucial gap in accessible yet detailed resources. This book not only contributes to the evolving field of neuroscience but also serves as a valuable guide for professionals, students, and informed laypersons seeking a deeper understanding of coffee's effects on brain health and overall well-being.In-Depth Exploration of Biochemical and Physiological Mechanisms: Investigate into the intricate biochemical and physiological processes that underscore the impact of coffee and its constituents, providing essential insights for professionals and students in neuroscience.Comprehensive Coverage of Mental Health and Neurodegenerative Diseases: Unique chapters dedicated to exploring coffee's relationship with mental health conditions and neurodegenerative diseases, offering valuable resources for healthcare professionals and individuals affected by these conditions.Balanced Perspective on Health Benefits and Risks: Presenting a nuanced analysis, the volume provides a comprehensive understanding of both the potential health benefits and risks associated with coffee consumption, empowering readers to make informed decisions about their coffee intake.

Neuroscience of Coffee, Volume 289 is a pioneering volume that delves into the intricate relationship between one of the world's most beloved beverages and the human brain. Offering a comprehensive exploration of the biochemical and physiological mechanisms underlying coffee's impact on the nervous system, this groundbreaking book transcends traditional coffee literature by focusing specifically on the neurological aspects. Chapters in this new release include Coffee and Parkinson's Disease, Coffee and Alzheimer's Disease, Coffee and Multiple Sclerosis (MS), Coffee and Amyotrophic lateral sclerosis (ALS), Exploring the Complex Relationship Between Caffeine Consumption and Schizophrenia: A Review of Epidemiological and Clinical Studies, and much more.Additional chapters explore Coffee, Antioxidants, and Brain Inflammation, Behavioral and Psychological Aspects of Coffee Consumption, From Bean to Brain: Coffee, Gray Matter, and Neuroprotection in Neurological Disorders Spectrum, and Synaptic Modulation by Coffee Compounds: Insights into Neural Plasticity.Provides an in-Depth Exploration of Biochemical and Physiological MechanismsInvestigates the intricate biochemical and physiological processes that underscore the impact of coffee and its constituents, providing essential insights for professionals and students in neuroscienceCovers Mental Health and Neurodegenerative DiseasesOffers valuable resources for healthcare professionals and individuals affected by these neurological and neurodegenerative conditions

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0.Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 discusses how to develop adaptive, robust, scalable, and reliable applications that can be used in solutions for day-to-day problems. It focuses on the two frontiers — Big Data and Cloud Computing – and reviews the advantages and consequences of utilizing Cloud Computing to tackle Big Data issues within the manufacturing and production sector as part of Industry 4.0. The book unites some of the top Big Data experts throughout the world who contribute their knowledge and expertise on the different aspects, approaches, and concepts related to new technologies and novel findings. Based on the latest technologies, the book offers case studies and covers the major challenges, issues, and advances in Big Data and Cloud Computing for Industry 4.0.By exploring the basic and high-level concepts, this book serves as a guide for those in the industry, while also helping beginners and more advanced learners understand both basic and more complex aspects of the synergy between Big Data and Cloud Computing.

The idea behind this book is to simplify the journey of aspiring readers and researchers to understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0.Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0 discusses how to develop adaptive, robust, scalable, and reliable applications that can be used in solutions for day-to-day problems. It focuses on the two frontiers — Big Data and Cloud Computing – and reviews the advantages and consequences of utilizing Cloud Computing to tackle Big Data issues within the manufacturing and production sector as part of Industry 4.0. The book unites some of the top Big Data experts throughout the world who contribute their knowledge and expertise on the different aspects, approaches, and concepts related to new technologies and novel findings. Based on the latest technologies, the book offers case studies and covers the major challenges, issues, and advances in Big Data and Cloud Computing for Industry 4.0.By exploring the basic and high-level concepts, this book serves as a guide for those in the industry, while also helping beginners and more advanced learners understand both basic and more complex aspects of the synergy between Big Data and Cloud Computing.

Unveil the next frontier in neurodegenerative disorder research with Integrating Neuroimaging, Computational Neuroscience, and Artificial Intelligence. This groundbreaking book goes beyond traditional approaches, utilizing the power of interdisciplinary integration to illuminate new pathways in diagnosis and treatment. From AI-driven diagnostics to computational neuroscience models, this book showcases the forefront of innovation. Join us in exploring the future of neurodegenerative care, where collaboration and cutting-edge technology converge to redefine possibilities.Key Features:Integrates diverse fields of research, from neuroimaging to computational neuroscience and Artificial Intelligence.Emphasizes the translation of research findings into practical applications, ultimately benefitting patients and clinical practice.Reviews the implementation of Artificial Intelligence and computational models in diagnostic settings.Elucidates the current state of translational neuroscience exploring potential areas for further research and collaboration, including personalized treatments and drug development.Contributions from an international team of experts from diverse disciplines.

Machine Learning Applications Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader’s active learning. Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective. Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on: Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processingSmart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rulesAI and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate changeIdentifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health recordsWith its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.

This book provides the reader with a thorough understanding of schizophrenia as a complex brain disorder by explaining the various aspects investigated for its cognizance from epigenetics to chemistry and physics to computational approaches.

This book provides the reader with a thorough understanding of schizophrenia as a complex brain disorder by explaining the various aspects investigated for its cognizance from epigenetics to chemistry and physics to computational approaches. The book covers the key notions of schizophrenia from a variety of facets such as neurogenetics, neurochemistry, neuropharmacology, neurobiology, psychotherapy, psychiatric treatment, cognitive studies, behavioral and societal studies, and computational neurosciences. Individual chapters are focused on crucial topics such as cognitive-behavioral therapy, brain functioning, computational neuroscience, neuro-imaging, and many more. This book explains each section and chapter with utmost clarity to maintain comprehensiveness for every kind of reader. This book covers various classical as well as recent topics from basic to advance level knowledge regarding schizophrenia. The book's contributions regarding its inclusivity of topics, comprehensiveness of language, diversity in knowledge, and focus on the subject will attract all kinds of readers. It can be considered a single comprehensive handy reference book for beginners, including medical students, neuroscientists, researchers, clinicians, and medical practitioners. Cognizance of Schizophrenia will be an invaluable asset for all who are involved in neuroscience research or clinical studies.

The book provides a thorough examination of the crucial connection between diet, cognitive aging, and dementia using a multidisciplinary approach.