jain deepak kumar (60 risultati)

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Condizione: New. In.

Paperback. Condizione: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Condizione: Neu. Antihypothyroidism activity of leaves of Cassia fistula Linn. on rats | Evaluation of Antihypothyroidism activity of leaves of Cassia fistula Linn. on rats | Deepak Kumar Jain (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659147760 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. Like New. book.

Paperback. Condizione: Like New. Like New. book.

paperback. Condizione: New. New. Ships from Multiple Locations. book.

Hardcover. Condizione: new. Hardcover. Taking a broad, multidisciplinary approach to the ethical, legal, and practical dimensions of developing AI, the book puts key issues such as bias, transparency, accountability, and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. This book can be read as a resource for those who want to be able to guide the development and deployment of responsibly controlled AI systems. The book puts key issues such as bias, transparency, accountability and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condizione: New.

Condizione: New.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Hardcover. Condizione: new. Hardcover. Taking a broad, multidisciplinary approach to the ethical, legal, and practical dimensions of developing AI, the book puts key issues such as bias, transparency, accountability, and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. This book can be read as a resource for those who want to be able to guide the development and deployment of responsibly controlled AI systems. The book puts key issues such as bias, transparency, accountability and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condizione: New. In.

Condizione: New.

Condizione: New. In.

Condizione: New.

Hardcover. Condizione: new. Hardcover. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Considering the interest of researchers and academicians, editors here aim to present this book in a multidimensional perspective that will be covering Healthcare Recommender Systems in depth, considering pattern recognition techniques using amalgamation of emerging technologies. It aims to cover all topics ranging from discussion of recommender system to efficient management to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and in order to achieve this, the book has been organized into various chapters.The prime focus of the book is to explore the various issues, challenges, and research directions of pattern recognition in Healthcare Recommender Systems. The table of contents is designed in a manner so as to provide the reader with a broad list of its applications. Additionally, the book addresses the transformations in the area of Healthcare Recommender Systems. Thus, the book plans to discuss the recent research trends and advanced topics in the field of healthcare automation system which will be of interest to industry experts, academicians and researchers working in this area. Hence, the editors aim is to cover diversity in the domain while achieving completeness. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condizione: new. Hardcover. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Considering the interest of researchers and academicians, editors here aim to present this book in a multidimensional perspective that will be covering Healthcare Recommender Systems in depth, considering pattern recognition techniques using amalgamation of emerging technologies. It aims to cover all topics ranging from discussion of recommender system to efficient management to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and in order to achieve this, the book has been organized into various chapters.The prime focus of the book is to explore the various issues, challenges, and research directions of pattern recognition in Healthcare Recommender Systems. The table of contents is designed in a manner so as to provide the reader with a broad list of its applications. Additionally, the book addresses the transformations in the area of Healthcare Recommender Systems. Thus, the book plans to discuss the recent research trends and advanced topics in the field of healthcare automation system which will be of interest to industry experts, academicians and researchers working in this area. Hence, the editors aim is to cover diversity in the domain while achieving completeness. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condizione: new. Hardcover. Taking a broad, multidisciplinary approach to the ethical, legal, and practical dimensions of developing AI, the book puts key issues such as bias, transparency, accountability, and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. This book can be read as a resource for those who want to be able to guide the development and deployment of responsibly controlled AI systems. The book puts key issues such as bias, transparency, accountability and privacy at center stage. From computer science through law and ethics into policy, it lays down the roadmap on which developers, data scientists, and policymakers could bring AI technologies properly attuned to societal values. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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

Hardcover. Condizione: Brand New. 350 pages. 9.18x6.12x9.21 inches. In Stock.

Condizione: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.

Condizione: New.

Condizione: New. 2023rd edition NO-PA16APR2015-KAP.

Condizione: New.

Hardcover. Condizione: new. Hardcover. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Considering the interest of researchers and academicians, editors here aim to present this book in a multidimensional perspective that will be covering Healthcare Recommender Systems in depth, considering pattern recognition techniques using amalgamation of emerging technologies. It aims to cover all topics ranging from discussion of recommender system to efficient management to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and in order to achieve this, the book has been organized into various chapters.The prime focus of the book is to explore the various issues, challenges, and research directions of pattern recognition in Healthcare Recommender Systems. The table of contents is designed in a manner so as to provide the reader with a broad list of its applications. Additionally, the book addresses the transformations in the area of Healthcare Recommender Systems. Thus, the book plans to discuss the recent research trends and advanced topics in the field of healthcare automation system which will be of interest to industry experts, academicians and researchers working in this area. Hence, the editors aim is to cover diversity in the domain while achieving completeness. The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condizione: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.

Buch. Condizione: Neu. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book explores the complete system perspective, underlying theories, modelling, and the applications of pattern recognition in Healthcare Recommender System. Considering the interest of researchers and academicians, editors here aim to present this book in a multidimensional perspective that will be covering Healthcare Recommender Systems in depth, considering pattern recognition techniques using amalgamation of emerging technologies. It aims to cover all topics ranging from discussion of recommender system to efficient management to recent research challenges and issues. Editors aim to present the book in a self-sufficient manner and in order to achieve this, the book has been organized into various chapters.The prime focus of the book is to explore the various issues, challenges, and research directions of pattern recognition in Healthcare Recommender Systems. The table of contents is designed in a manner so as to provide the reader with a broad list of its applications. Additionally, the book addresses the transformations in the area of Healthcare Recommender Systems. Thus, the book plans to discuss the recent research trends and advanced topics in the field of healthcare automation system which will be of interest to industry experts, academicians and researchers working in this area. Hence, the editors aim is to cover diversity in the domain while achieving completeness.

Taschenbuch. Condizione: 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.