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Deep Learning in Healthcare: Paradigms and Applications: 171 (Intelligent Systems Reference Library) - Tapa dura
Sinopsis
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.
Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.
Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
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De la contraportada
This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.
Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.
Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer
- Año de publicación2019
- ISBN 10 3030326055
- ISBN 13 9783030326050
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de edición1
- Número de páginas234
- EditorChen Yen-Wei, Jain Lakhmi C.
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Deep Learning in Healthcare.
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Cham, Springer., 2020
ISBN 10: 3030326055
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xiv, 218 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Nº de ref. del artículo: 7701FB
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Deep Learning in Healthcare
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Springer International Publishing, 2019
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Discusses the advances and future of deep learning in medicine and health careIncludes a comprehensiveCC  introduction to deep learningFocuses on medical imaging and computer-aided diagnosisThis book provides a comprehen. Nº de ref. del artículo: 448679072
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Deep Learning in Healthcare: Paradigms and Applications (Intelligent Systems Reference Library, 171)
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Deep Learning in Healthcare
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Springer International Publishing Nov 2019, 2019
ISBN 10: 3030326055
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques. 232 pp. Englisch. Nº de ref. del artículo: 9783030326050
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Deep Learning in Healthcare : Paradigms and Applications
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Springer International Publishing, 2019
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ISBN 13: 9783030326050
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques. Nº de ref. del artículo: 9783030326050
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Deep Learning in Healthcare : Paradigms and Applications
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Deep Learning in Healthcare
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Springer International Publishing, Springer Nature Switzerland Nov 2019, 2019
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems.Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data.Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch. Nº de ref. del artículo: 9783030326050
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