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Taschenbuch. Zustand: Neu. Health Information Science | 10th International Conference, HIS 2021, Melbourne, VIC, Australia, October 25-28, 2021, Proceedings | Siuly Siuly (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xii | Englisch | 2021 | Springer | EAN 9783030908843 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the 10th International Conference on Health Information Science, HIS 2021, which took place in Melbourne, Australia, in October 2021.The 16 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 56 submissions. They are organized in topical sections named: COVID-19, EEG data processing, Medical Data Analysis, Medical Record Mining (I), Medical Data Mining (II), Medical Data Processing.

Zustand: New. pp. 370.

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Zustand: New. Introduces the mathematical model and concepts of neutrosophic theory and methods Highlights the different techniques of neutrosophic theory, focusing on applying the neutrosophic set in image analysis to support computer- aided diagnosis .

Taschenbuch. Zustand: Neu. Data Analysis for Neurodegenerative Disorders | Deepika Koundal (u. a.) | Taschenbuch | Cognitive Technologies | viii | Englisch | 2024 | Springer | EAN 9789819921560 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: New. Presents the latest mathematical models of microwave and RF ablation theories Discusses the biological responses and engineering principles by which thermal ablation techniques can provide temperature-elevation within the organs of the hum.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders.This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the challenges involved in handling medical big data in the diagnosis of neurological disorders. It discusses how to optimally reduce the number of neuropsychological tests during the classification of these disorders by using feature selection methods based on the diagnostic information of enrolled subjects. The book includes key definitions/models and covers their applications in different types of signal/image processing for neurological disorder data. An extensive discussion on the possibility of enhancing the abilities of AI systems using the different data analysis is included. The book recollects several applicable basic preliminaries of the different AI networks and models, while also highlighting basic processes in image processing for various neurological disorders. It also reports on several applications to image processing and explores numerous topics concerning the role of big data analysis in addressing signal and image processing in various real-world scenarios involving neurological disorders.This cutting-edge book highlights the analysis of medical data, together with novel procedures and challenges for handling neurological signals and images. It will help engineers, researchers and software developers to understand the concepts and different models of AI and data analysis. To help readers gain a comprehensive grasp of the subject, it focuses on three key features: Presents outstanding concepts and models for using AI in clinical applications involving neurological disorders, with clear descriptions of image representation, feature extraction and selection. Highlights a range of techniques for evaluating the performance of proposed CAD systems for the diagnosis of neurological disorders. Examines various signal and image processing methods for efficient decision support systems. Soft computing, machine learning and optimization algorithms are also included to improve the CAD systems used.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides current state of the art along with an insight of recent research trends and open issues, challenges, and future research direction for the academician, analyzer, researcher, writers, and authors. It also provides an opportunity to exchange knowledge in the field of IoT-enabled smart systems, Industry 4.0, networking, cyber-physical system, computing paradigms, and security with various tools and methods used for industry-oriented intelligent-based IoT applications. This advanced research edited book focuses on emerging and advancing technology-federated machine learning, blockchain, and artificial intelligence for real-time Internet of things (IoT) application to solve the real-world problems and make the life of human more conformable. The objective of the proposed book is to develop privacy preserving model for IoT applications and improve the security, privacy, reliability, and sustainability of the systems. This book motivates and enhances the quality of research and commercialization in the fields of AI, Industry 4.0, federated learning, and blockchain.

Hardcover. Zustand: Brand New. 275 pages. 9.25x6.10x0.69 inches. In Stock.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 376 | Sprache: Englisch | Produktart: Bücher | Digital technology has enabled a number of internet-enabled devices that generate huge volumes of data from different systems. This large amount of heterogeneous data requires efficient data collection, processing, and analytical methods. Deep Learning is one of the latest efficient and feasible solutions that enable smart devices to function independently with a decision-making support system. Convergence of Deep Learning and Internet of Things: Computing and Technology contributes to technology and methodology perspectives in the incorporation of deep learning approaches in solving a wide range of issues in the IoT domain to identify, optimize, predict, forecast, and control emerging IoT systems. Covering topics such as data quality, edge computing, and attach detection and prediction, this premier reference source is a comprehensive resource for electricians, communications specialists, mechanical engineers, civil engineers, computer scientists, students and educators of higher education, librarians, researchers, and academicians.

Taschenbuch. Zustand: Neu. Neuware - Neutrosophic Set in Medical Image Analysis gives an understanding of the concepts of NS, along with knowledge on how to gather, interpret, analyze and handle medical images using NS methods. It presents the latest cutting-edge research that gives insight into neutrosophic set's novel techniques, strategies and challenges, showing how it can be used in biomedical diagnoses systems. The neutrosophic set (NS), which is a generalization of fuzzy set, offers the prospect of overcoming the restrictions of fuzzy-based approaches to medical image analysis.