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Machine learning and artificial intelligence use cases in healthcare presented in the book give researchers, practitioners, and students a wide range of practical examples of cross-domain convergence.\u003c\/p\u003e\u003cp\u003eThe wide variety of topics covered include:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eArtificial Intelligence in healthcare\u003c\/li\u003e\n\u003cli\u003eMachine learning solutions for such disease as diabetes, arthritis, cardiovascular disease, and COVID-19\u003c\/li\u003e\n\u003cli\u003eBig data analytics solutions for healthcare data processing\u003c\/li\u003e\n\u003cli\u003eReliable biomedical applications using AI models\u003c\/li\u003e\n\u003cli\u003eIntelligent IoT in healthcare\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThe book explains fundamental concepts as well as the advanced use cases, illustrating how to apply emerging technologies such as machine learning, AI models, and data informatics into practice to tackle challenges in the field of healthcare with real-world scenarios. 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Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eSoft Computing Principles and Integration for Real-Time Service-Oriented Computing\u003c\/b\u003e explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. 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As this book demonstrates, algorithms, and mechanisms of self-organization of complex natural systems have been used to solve optimization problems, particularly in complex systems that are adaptive, ever-evolving, and distributed in nature.\u003c\/p\u003e\u003cp\u003eThe chapters look at ways of enhancingto enhance the performance of fog networks in real-world applications using nature-based optimization techniques. They discuss challenges and provide solutions to the concerns of security, privacy, and power consumption in cloud data center nodes and fog computing networks. The book also examines how:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eThe existing fog and edge architecture is used to provide solutions to future challenges.\u003c\/li\u003e\n\u003cli\u003eA geographical information system (GIS) can be used with fog computing to help users in an urban region access prime healthcare.\u003c\/li\u003e\n\u003cli\u003eAn optimization framework helps in cloud resource management.\u003c\/li\u003e\n\u003cli\u003eFog computing can improve the quality, quantity, long-term viability, and cost-effectiveness in agricultural production.\u003c\/li\u003e\n\u003cli\u003eVirtualization can support fog computing, increase resources to be allocated, and be applied to different network layers.\u003c\/li\u003e\n\u003cli\u003eThe combination of fog computing and IoT or cloud computing can help healthcare workers predict and analyze diseases in patients.\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"WoB","offers":[{"title":"US \/ NEW \/ INGRAM","offer_id":51284979286289,"sku":"NIN9781032345895","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52593308434705,"sku":"NLS9781032345895","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1032345896.jpg?v=1788536358"},{"product_id":"healthcare-solutions-using-machine-learning-and-informatics-book-punit-gupta-9781032201986","title":"Healthcare Solutions Using Machine Learning and Informatics","description":"Focuses on fundamental concepts of gathering, processing, analyzing the dataset from rich healthcare and biomedical sources. 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With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition.\u003c\/p\u003e\u003cp\u003eThis book discusses the future improvements and possible intelligent optimization models using artificial intelligence, deep learning techniques and other hybrid models to improve the performance of cloud. 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