Handbook of Statistical Analysis: AI and ML Applications, Third Edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business problems, weigh the strengths and weaknesses of modern data analysis algorithms, and employ the right analytical methods for practical application. This resource is an ideal guide for users who want to address massive and complex datasets with many standard analytical approaches and be able to evaluate analyses and solutions objectively. It includes clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques; offers accessible tutorials; and discusses their application to real-world problems.
Data Analytics for Intelligent Transportation Systems, Second Edition provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Other sections provide extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies.All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. In addition, they will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning.
Medical Oncology Compendium discusses several important topics in oncology by leading experts worldwide who incorporates not only knowledge on recent developments in the field, but contextualize them within diverse socio-economic environments to guarantee the applicability of the content in challenging scenarios. It comprehensively discusses topics such as surgery, radiology, carcinogenesis, screening, assessment tools, evidence-based medicine, and precision oncology as applicable to different cancer types as non-small and small cell lung cancer, mesothelioma, breast cancer, gastric-rectal cancer, female specific cancers, prostate, skin and bone sarcomas. In addition, it discusses options to minimize oncology pain and palliative care. It is a valuable resource for oncologists, clinicians, researchers, healthcare workers and members of biomedical field who needs to understand more about diagnosis, treatment options and support for cancer patients.
Ali Ahmadian, Soheil Salahshour, Valentina Emila Balas + 1 more
September 1, 2024
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Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science.
Harish Garg, Jyotir Moy Chatterjee, R Sujatha + 1 more
September 1, 2024
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Primer to Neuromorphic Computing highlights critical and ongoing research into the diverse applications of neuromorphic computing. It includes an overview of primary scientific concepts for the research topic of neuromorphic computing, such as neurons as computational units, artificial intelligence, machine learning and neuromorphic models. It also discusses the fundamental design method and organization of neuromorphic architecture.Hardware for neuromorphic systems can be developed by exploiting the magnetic properties of different materials. These systems are more energy efficient and enable faster computation . Magnetic tunnel junctions and magnetic textures can be employed to act as neurons and synapses. Neuromorphic systems have general intelligence like humans as they can apply knowledge gained in one domain to other domains.
Computational Knowledge Vision: The First Footprints presents a novel advanced framework which combines structuralized knowledge and visual models—Computational Knowledge Vision. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determine whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception.Computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems. Currently, computer vision systems are highly specialized and very limited in their ability to do visual reasoning and causal inference. We need task-specific designs and large amounts of labeled training data for model training. However, the models trained in this way still lack a general understanding of common sense that is obvious to the average adult and cannot describe the workings of our physical and social worlds. Humans can thoroughly understand visual scenes because of priori knowledge from many domains and can learn and reason effectively based on their knowledge. Questions naturally arise (1) how can human knowledge be incorporated with visual models? (2) how does human knowledge promote the performance of visual models? To address these problems, Computational Knowledge Vision: The First Footprints proposes a new framework for computer vision– computational knowledge vision.
The Evolution of Immunotherapy Against Tumors: An Historical Approach summarizes the literature concerning the development of the theory of immune surveillance against tumors. It discusses the evidence for and against this theory, along with the concept of immunoediting. Finally, current approaches in anti-tumor immunotherapy will be analyzed.The immune system plays a major role in the surveillance against tumors. To avoid attack from the immune system, tumor cells develop different strategies to escape immune surveillance. Evidence of immune surveillance comes from both animal models and clinical observations. Mice with a wide variety of immunodeficiencies have a high rate of tumor incidence and are more susceptible to transplanted or chemical carcinogen-induced tumors. Immunosuppressed patients have a high incidence of tumors. However, many patients develop cancer even in the presence of an apparently normal immune system. This indicates that tumor cells can escape immune surveillance.
Valentina Rapozzi, Luigi Xodo and Benjamin Bonavida
September 1, 2024
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Therapeutic Applications of Nitric Oxide in Cancer and Inflammatory Diseases: Third International Conference on Therapeutic Application of Nitric Oxide in Cancer and Inflammatory Disorders presents updated information on the chemistry, signaling of newly derived therapeutic nitric oxide donors/inhibitors, and their complexes in liposomes or nanospheres in both pre-clinical and clinical activities.In six parts It discusses many examples of research related to the application of novel therapeutic compounds that focus on a chemical, nitric oxide, and their applications that have been shown to exert significant therapeutic activities against various resistant cancers unresponsive to current treatments, and different inflammatory diseases which continue to require novel treatments.It is a valuable resource for cancer researchers, oncologists, graduate students, and researchers from medical and biomedical fields who want to know more about NO and its therapeutic applications in cancer and inflammatory diseases. It is highly useful for both scientists and clinicians as well as pharmaceutical companies involved in the development of new anticancer/anti-inflammatory agents.
Moving Towards Everlasting Artificial Intelligent Battery-Powered Implants presents the development process of new artificial intelligent charging systems for battery powered implants that can last for a lifetime after implantation. This book introduces new strategies to address the limitations of technologies that have been employed to improve the lifespan of medical implants. This book also provides guidelines that medical implant manufacturers can adopt during their product development stages - this adds a new dimension of research on medical device implants that can be a game changer for the artificial intelligent (AI) medical implants industry. Researchers, engineers, and graduate students in the fields of biomedical engineering, electrical engineering, and computer science will find this text helpful as they seek to understand the potential of AI systems to help achieve sustainability in healthcare and make current medical implants relevant in the future.
Advances in Cancer Biomarkers Research provides a thorough and detailed description of cancer biomarkers for diagnostic, prognostic and therapeutics in several cancer types. The book presents a compendium of topics related to current advanced research, along with fundamental knowledge that will help readers fully comprehend the field of cancer biomarkers. Topics discussed include such the role of genetic mechanisms, epigenetics, DNA and microRNA in different cancers, signaling pathways and exosomes. In addition, the book discusses biomarker research applied to several cancer types, such as head and neck, urological, lung, bone tumors, hematological and neurological malignancies and breast cancers.This will be a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of biomarkers in cancer research and treatment.