Isbn: 9783030716752 - deep learning for biomedical data analysis: techniques, approaches, and applications (11 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis.The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries.…

  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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  • Sprache: Englisch

    Verlag: Springer Nature, 2021

    3030716759 / 9783030716752

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    Hardcover. Zustand: Brand New. 365 pages. 9.25x6.10x1.06 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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  • Sprache: Englisch

    Verlag: Springer International Publishing Jul 2021, 2021

    3030716759 / 9783030716752

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    Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis.The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries. 368 pp. Englisch.…

  • Sprache: Englisch

    Verlag: Springer International Publishing, 2021

    3030716759 / 9783030716752

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    Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Surveys the most recent techniques and approaches in the field of Deep Learning and biomedical data analysisOffers enough fundamental and technical information on Deep Learning techniques, approaches and the related problems.…

  • Sprache: Englisch

    Verlag: Springer, Springer Jul 2021, 2021

    3030716759 / 9783030716752

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    Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -1-Dimensional Convolution Neural Network Classification Technique for Gene Expression Data.- Classification of Sequences with Deep Artificial Neural Networks: Representation and Architectural Issues.- A Deep Learning Model for MicroRNA-Target Binding.- Recurrent Neural Networks Architectures for Accidental Fall Detection on Wearable Embedded Devices.- Medical Image Retrieval System using Deep Learning Techniques.- Medical Image Fusion using Deep Learning.- Deep Learning for Histopathological Image Analysis.- Innovative Deep Learning Approach for Biomedical Data Instantiation and Visualization.- Convolutional Neural Networks in Advanced Biomedical Imaging Applications.- Deep Learning for Lung Disease Detection from Chest X-Rays Images.- Deep Learning in Multi-Omics Data Integration in Cancer Diagnostic.- Using Deep Learning with Canadian Primary Care Data for Disease Diagnosis.- Brain Tumor Segmentation and Surveillance with Deep Artificial Neural Networks.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 368 pp. Englisch.…

  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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  • Sprache: Englisch

    Verlag: Springer, 2021

    3030716759 / 9783030716752

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