Advanced Machine Learning Approaches in Cancer Prognosis: Challenges and Applications (Intelligent Systems Reference Library)
ISBN 10: 3030719774 ISBN 13: 9783030719777
Edité par Springer, 2022
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This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.
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Titre : Advanced Machine Learning Approaches in ...
Éditeur : Springer
Date d'édition : 2022
Reliure : Couverture souple
Etat : New
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Advanced Machine Learning Approaches in Cancer Prognosis
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Springer International Publishing, 2022
ISBN 10 : 3030719774
ISBN 13 : 9783030719777
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses all types of cancer diseases information with their detection, solution, and preventionPresents advanced machine learning approaches spanning the areas of neural networks, fuzzy logic, connectionist systems, genetic algorithms, evolution. N° de réf. du vendeur 600116245
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Advanced Machine Learning Approaches in Cancer Prognosis: Challenges and Applications (Intelligent Systems Reference Library)
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Advanced Machine Learning Approaches in Cancer Prognosis: Challenges and Applications (Intelligent Systems Reference Library)
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Advanced Machine Learning Approaches in Cancer Prognosis (Paperback)
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Springer Nature Switzerland AG, Cham, 2022
ISBN 10 : 3030719774
ISBN 13 : 9783030719777
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Paperback. Etat : new. Paperback. This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed. This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783030719777
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Advanced Machine Learning Approaches in Cancer Prognosis
ISBN 10 : 3030719774
ISBN 13 : 9783030719777
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Taschenbuch. Etat : Neu. Neuware -This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 476 pp. Englisch. N° de réf. du vendeur 9783030719777
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Advanced Machine Learning Approaches in Cancer Prognosis : Challenges and Applications
Edité par
Springer International Publishing, 2022
ISBN 10 : 3030719774
ISBN 13 : 9783030719777
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic,and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learninghaveproved its vast range of significance and,provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D.students, postdocs, and anyone interested in the subjects discussed. N° de réf. du vendeur 9783030719777
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Advanced Machine Learning Approaches in Cancer Prognosis
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Springer International Publishing Mai 2022, 2022
ISBN 10 : 3030719774
ISBN 13 : 9783030719777
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Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic,and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learninghaveproved its vast range of significance and,provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D.students, postdocs, and anyone interested in the subjects discussed. 476 pp. Englisch. N° de réf. du vendeur 9783030719777
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Advanced Machine Learning Approaches in Cancer Prognosis: Challenges and Applications (Intelligent Systems Reference Library)
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