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Author: Guangchuang Yu
Publisher: Frontiers Media SA
ISBN: 2889761908
Category : Science
Languages : en
Pages : 146
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Book Description
Author: Guangchuang Yu
Publisher: Frontiers Media SA
ISBN: 2889761908
Category : Science
Languages : en
Pages : 146
Get Book Here
Book Description
Author: Mourad Elloumi
Publisher: Springer Nature
ISBN: 3030716767
Category : Medical
Languages : en
Pages : 358
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Book Description
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.
Author: Matthew O. Ward
Publisher: CRC Press
ISBN: 1482257386
Category : Computers
Languages : en
Pages : 571
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Book Description
An Updated Guide to the Visualization of Data for Designers, Users, and ResearchersInteractive Data Visualization: Foundations, Techniques, and Applications, Second Edition provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. In color throughout, it explains basic terminology
Author: Gintautas Dzemyda
Publisher: Springer Science & Business Media
ISBN: 1441902368
Category : Mathematics
Languages : en
Pages : 262
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Book Description
This book highlights recent developments in multidimensional data visualization, presenting both new methods and modifications on classic techniques. Throughout the book, various applications of multidimensional data visualization are presented including its uses in social sciences (economy, education, politics, psychology), environmetrics, and medicine (ophthalmology, sport medicine, pharmacology, sleep medicine). The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions are discussed. The utilization of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed. The book includes over 100 detailed images presenting examples of the many different visualization techniques that the book presents. This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.
Author: Paul M. Rea
Publisher: Springer
ISBN: 3030060705
Category : Medical
Languages : en
Pages : 142
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Book Description
This edited volume explores the use of technology to enable us to visualise the life sciences in a more meaningful and engaging way. It will enable those interested in visualisation techniques to gain a better understanding of the applications that can be used in imaging and analysis, education, engagement and training. The reader will be able to explore the utilisation of technologies from a number of fields to enable an engaging and meaningful visual representation of the life sciences. This use of technology-enhanced learning will be of benefit for the learner, trainer, in patient care and the wider field of education and engagement. By examining a range of techniques in image capture (photogrammetery, stereophotogrammetry, microphotogrammetry and autostereoscopy), this book will showcase the wide range of tools we can use. Researchers in this field will be able to find something suitable to apply to their work to enhance user engagement through improved visual means using the technologies we have available to us today. It will highlight the uses of these technologies to examine many aspects of the human body, and enable improved ways to enhance visual and tactile learning, including 3D printing. By demonstrating co-design processes, working directly with the end-stage users (including patients), it will also highlight successes in adopting tools like hand motion tracking rehabilitation for patients with conditions like multiple sclerosis. The book will also discuss the applications of immersive environments including virtual, augmented and mixed reality. The ultimate aim is to show how, by using these tools, we can enhance communication, mobile applications, health literacy and illustration of both normal and pathological processes in the body. By applying a wide range of tools and technologies, this volume will highlight the wide range of applications in education, training and learning both for students and faculty, but also for patient care and education. Therefore, the work presented here can be accessed by a wide range of users from faculty and students involved in the design and development of these processes, by examining the pedagogy around these technologies. Importantly, it presents material, which will be of benefit for the patient, engaging them to become more involved with techniques like physiotherapy.
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1498775861
Category : Mathematics
Languages : en
Pages : 537
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Book Description
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Author: Kun Chang Lee
Publisher: Academic Press
ISBN: 0128193158
Category : Science
Languages : en
Pages : 298
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Book Description
Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. - Examines the development and application of data analytics applications in biomedical data - Presents innovative classification and regression models for predicting various diseases - Discusses genome structure prediction using predictive modeling - Shows readers how to develop clinical decision support systems - Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks
Author: Bernhard Preim
Publisher: Newnes
ISBN: 0124159796
Category : Computers
Languages : en
Pages : 1017
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Book Description
Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment. The book includes algorithms, applications, and ideas on achieving reliability of results and clinical evaluation of the techniques covered. Preim and Botha illustrate visualization techniques from research, but also cover the information required to solve practical clinical problems. They base the book on several years of combined teaching and research experience. This new edition includes six new chapters on treatment planning, guidance and training; an updated appendix on software support for visual computing for medicine; and a new global structure that better classifies and explains the major lines of work in the field. - Complete guide to visual computing in medicine, fully revamped and updated with new developments in the field - Illustrated in full color - Includes a companion website offering additional content for professors, source code, algorithms, tutorials, videos, exercises, lessons, and more
Author: Hamish Carr
Publisher: Springer Nature
ISBN: 3030430367
Category : Mathematics
Languages : en
Pages : 264
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Book Description
This collection of peer-reviewed workshop papers provides comprehensive coverage of cutting-edge research into topological approaches to data analysis and visualization. It encompasses the full range of new algorithms and insights, including fast homology computation, comparative analysis of simplification techniques, and key applications in materials and medical science. The book also addresses core research challenges such as the representation of large and complex datasets, and integrating numerical methods with robust combinatorial algorithms. In keeping with the focus of the TopoInVis 2017 Workshop, the contributions reflect the latest advances in finding experimental solutions to open problems in the sector. They provide an essential snapshot of state-of-the-art research, helping researchers to keep abreast of the latest developments and providing a basis for future work. Gathering papers by some of the world’s leading experts on topological techniques, the book represents a valuable contribution to a field of growing importance, with applications in disciplines ranging from engineering to medicine.
Author: Frits H. Post
Publisher: Springer Science & Business Media
ISBN: 1461511771
Category : Computers
Languages : en
Pages : 445
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Book Description
Data visualization is currently a very active and vital area of research, teaching and development. The term unites the established field of scientific visualization and the more recent field of information visualization. The success of data visualization is due to the soundness of the basic idea behind it: the use of computer-generated images to gain insight and knowledge from data and its inherent patterns and relationships. A second premise is the utilization of the broad bandwidth of the human sensory system in steering and interpreting complex processes, and simulations involving data sets from diverse scientific disciplines and large collections of abstract data from many sources. These concepts are extremely important and have a profound and widespread impact on the methodology of computational science and engineering, as well as on management and administration. The interplay between various application areas and their specific problem solving visualization techniques is emphasized in this book. Reflecting the heterogeneous structure of Data Visualization, emphasis was placed on these topics: -Visualization Algorithms and Techniques; -Volume Visualization; -Information Visualization; -Multiresolution Techniques; -Interactive Data Exploration. Data Visualization: The State of the Art presents the state of the art in scientific and information visualization techniques by experts in this field. It can serve as an overview for the inquiring scientist, and as a basic foundation for developers. This edited volume contains chapters dedicated to surveys of specific topics, and a great deal of original work not previously published illustrated by examples from a wealth of applications. The book will also provide basic material for teaching the state of the art techniques in data visualization. Data Visualization: The State of the Art is designed to meet the needs of practitioners and researchers in scientific and information visualization. This book is also suitable as a secondary text for graduate level students in computer science and engineering.
