deep learning biomedical applications (33 Ergebnisse)

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Zustand: New.

Paperback. Zustand: Brand New. 364 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Zustand: Brand New. 224 pages. 9.19x6.13x0.51 inches. In Stock.

Taschenbuch. Zustand: Neu. Deep Learning for Biomedical Applications | Utku Kose (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032033235 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Zustand: New.

Zustand: New.

Zustand: New. pp. 332.

Zustand: New. pp. 270.

Zustand: New.

Paperback. Zustand: Brand New. 344 pages. 9.19x6.13x0.78 inches. In Stock.

Zustand: New.

Zustand: New.

Paperback. Zustand: Brand New. 330 pages. 9.25x7.50x8.96 inches. In Stock.

Hardcover. Zustand: Brand New. 232 pages. 9.75x6.50x0.75 inches. In Stock.

Taschenbuch. Zustand: Neu. Deep Learning and Other Soft Computing Techniques | Biomedical and Related Applications | Nguyen Hoang Phuong (u. a.) | Taschenbuch | ix | Englisch | 2024 | Springer | EAN 9783031294495 | 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 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.

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.

Zustand: New. Inhaltsverzeichnis1. Introduction to Deep Learning and Diagnosis in Medicine2. 1D CNN based identification of Sleep disorders using EEG signals3. Classification of Histopathological Colon Cancer Images Using PSO based Feature Sel.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the use of artificial intelligence (AI) and computationalintelligence (CI) in medical and related applications. Applications includeall aspects of medicine: from diagnostics (including analysis of medicalimages and medical data) to therapeutics (including drug designand radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning),techniques for processing expert knowledge (e.g., fuzzy techniques), andadvanced techniques of applied mathematics (such as innovative probabilisticand graph-based techniques).The book also shows that these techniques can be used in many otherapplications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI andCI methods and their biomedical (and related) applications-and to furtherdevelop thisimportant research direction.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book focuses on the use of artificial intelligence (AI) and computationalintelligence (CI) in medical and related applications. Applications includeall aspects of medicine: from diagnostics (including analysis of medicalimages and medical data) to therapeutics (including drug designand radiotherapy) to epidemic- and pandemic-related public health policies.Corresponding techniques include machine learning (especially deep learning),techniques for processing expert knowledge (e.g., fuzzy techniques), andadvanced techniques of applied mathematics (such as innovative probabilisticand graph-based techniques).The book also shows that these techniques can be used in many otherapplications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI andCI methods and their biomedical (and related) applications-and to furtherdevelop thisimportant research direction.

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

Zustand: New.

Hardcover. Zustand: Brand New. 300 pages. 9.25x6.10x0.71 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize deep learning models with computer vision. Deep learning is integrated with computer vision to enhance the performance of image classification with localization, object detection, object recognition, object segmentation, image style transfer, image colorization, image reconstruction, image super-resolution, image synthesis, motion detection, pose estimation, semantic segmentation in biomedical field. Huge number of efficient approaches/applications and models support medical decisions in the fields of cardiology, dermatology, and radiology. The content of book elaborates deep learning models such as convolution neural networks, deep learning, generative adversarial network, long short-term memory networks (LSTM), autoencoder (AE), restricted Boltzmann machine (RBM), self-organizing map (SOM), deep belief network (DBN), etc.

Hardcover. Zustand: Brand New. 1st edition. 347 pages. 9.50x6.25x1.00 inches. In Stock.

Hardcover. Zustand: Brand New. 250 pages. 9.25x6.10x9.44 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware - Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases.

Hardcover. Zustand: Brand New. 384 pages. 9.19x6.13x0.88 inches. In Stock.