handbook of data science approaches for biomedical engineering

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Handbook of Data Science Approaches for Biomedical Engineering
Author : Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Manju Khari
Publisher : Academic Press
Release Date : 2019-11-13
ISBN 10 : 0128183195
Pages : 318 pages
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Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Data Deduplication Approaches
Author : Tin Thein Thwel,G. R. Sinha
Publisher : Academic Press
Release Date : 2020-11-25
ISBN 10 : 0128236337
Pages : 404 pages
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In the age of data science, the rapidly increasing amount of data is a major concern in numerous applications of computing operations and data storage. Duplicated data or redundant data is a main challenge in the field of data science research. Data Deduplication Approaches: Concepts, Strategies, and Challenges shows readers the various methods that can be used to eliminate multiple copies of the same files as well as duplicated segments or chunks of data within the associated files. Due to ever-increasing data duplication, its deduplication has become an especially useful field of research for storage environments, in particular persistent data storage. Data Deduplication Approaches provides readers with an overview of the concepts and background of data deduplication approaches, then proceeds to demonstrate in technical detail the strategies and challenges of real-time implementations of handling big data, data science, data backup, and recovery. The book also includes future research directions, case studies, and real-world applications of data deduplication, focusing on reduced storage, backup, recovery, and reliability. Includes data deduplication methods for a wide variety of applications Includes concepts and implementation strategies that will help the reader to use the suggested methods Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable methods for their applications Focuses on reduced storage, backup, recovery, and reliability, which are the most important aspects of implementing data deduplication approaches Includes case studies

Internet of Things for Healthcare Technologies
Author : Chinmay Chakraborty,Amit Banerjee,Maheshkumar H. Kolekar,Lalit Garg,Basabi Chakraborty
Publisher : Springer Nature
Release Date : 2020-06-08
ISBN 10 : 9811541124
Pages : 324 pages
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This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals’ steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to better quality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.

Web Information Systems Engineering – WISE 2020
Author : Zhisheng Huang,Wouter Beek,Hua Wang,Rui Zhou,Yanchun Zhang
Publisher : Springer Nature
Release Date : 2020-10-20
ISBN 10 : 3030620085
Pages : 610 pages
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This book constitutes the proceedings of the 21st International Conference on Web Information Systems Engineering, WISE 2020, held in Amsterdam, The Netherlands, in October 2020. The 81 full papers presented were carefully reviewed and selected from 190 submissions. The papers are organized in the following topical sections: Part I: network embedding; graph neural network; social network; graph query; knowledge graph and entity linkage; spatial temporal data analysis; and service computing and cloud computing Part II: information extraction; text mining; security and privacy; recommender system; database system and workflow; and data mining and applications

Handbook of Deep Learning in Biomedical Engineering
Author : Valentina Emilia Balas,Brojo Kishore Mishra,Raghvendra Kumar
Publisher : Academic Press
Release Date : 2020-11-23
ISBN 10 : 0128230479
Pages : 320 pages
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Deep learning (DL) is a method of machine learning, running over artificial neural networks, that uses multiple layers to extract high-level features from large amounts of raw data. DL methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of DL and its applications in the field of biomedical engineering. DL has been rapidly developed in recent years, in terms of both methodological constructs and practical applications. DL provides computational models of multiple processing layers to learn and represent data with higher levels of abstraction. It is able to implicitly capture intricate structures of large-scale data and is ideally suited to many of the hardware architectures that are currently available. The ever-expanding amount of data that can be gathered through biomedical and clinical information sensing devices necessitates the development of machine learning and artificial intelligence techniques such as DL and convolutional neural networks to process and evaluate the data. Some examples of biomedical and clinical sensing devices that use DL include computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic particle imaging, electroencephalography/magnetoencephalography (EE/MEG), optical microscopy and tomography, photoacoustic tomography, electron tomography, and atomic force microscopy. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications provides the most complete coverage of DL applications in biomedical engineering available, including detailed real-world applications in areas such as computational neuroscience, neuroimaging, data fusion, medical image processing, neurological disorder diagnosis for diseases such as Alzheimer’s, attention deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), tumor prediction, and translational multimodal imaging analysis. Presents a comprehensive handbook of the biomedical engineering applications of DL, including computational neuroscience, neuroimaging, time series data such as MRI, functional MRI, CT, EEG, MEG, and data fusion of biomedical imaging data from disparate sources, such as X-Ray/CT. Helps readers understand key concepts in DL applications for biomedical engineering and health care, including manifold learning, classification, clustering, and regression in neuroimaging data analysis. Provides readers with key DL development techniques such as creation of algorithms and application of DL through artificial neural networks and convolutional neural networks. Includes coverage of key application areas of DL such as early diagnosis of specific diseases such as Alzheimer’s, ADHD, and ASD, and tumor prediction through MRI and translational multimodality imaging and biomedical applications such as detection, diagnostic analysis, quantitative measurements, and image guidance of ultrasonography. ~

Handbook of Artificial Intelligence in Biomedical Engineering
Author : Saravanan Krishnan,Ramesh Kesavan,B. Surendiran,G.S. Mahalakshmi
Publisher : CRC Press
Release Date : 2021-03-30
ISBN 10 : 100006767X
Pages : 538 pages
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Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert’s knowledge in order to predict and monitor the health status in real time. The accuracy of the AI systems is drastically increasing by using machine learning, digitized medical data acquisition, wireless medical data communication, and computing infrastructure AI approaches, helping to solve complex issues in the biomedical industry and playing a vital role in future healthcare applications. The volume takes a multidisciplinary perspective of employing these new applications in biomedical engineering, exploring the combination of engineering principles with biological knowledge that contributes to the development of revolutionary and life-saving concepts.

Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science
Author : Raj, Pethuru,Raman, Anupama
Publisher : IGI Global
Release Date : 2018-05-18
ISBN 10 : 1522559736
Pages : 440 pages
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Fog computing is quickly increasing its applications and uses to the next level. As it continues to grow, different types of virtualization technologies can thrust this branch of computing further into mainstream use. The Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science is a key reference volume on the latest research on the role of next-generation systems and devices that are capable of self-learning and how those devices will impact society. Featuring wide-ranging coverage across a variety of relevant views and themes such as cognitive analytics, data mining algorithms, and the internet of things, this publication is ideally designed for programmers, IT professionals, students, researchers, and engineers looking for innovative research on software-defined cloud infrastructures and domain-specific analytics.

Handbook of Neuroimaging Data Analysis
Author : Hernando Ombao,Martin Lindquist,Wesley Thompson,John Aston
Publisher : CRC Press
Release Date : 2016-11-18
ISBN 10 : 1482220989
Pages : 662 pages
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This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.

Biomedical Engineering Handbook 2
Author : Joseph D. Bronzino
Publisher : Springer Science & Business Media
Release Date : 2000-02-15
ISBN 10 : 9783540668084
Pages : 329 pages
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Handbook of Big Data Analytics
Author : Wolfgang Karl Härdle,Henry Horng-Shing Lu,Xiaotong Shen
Publisher : Springer
Release Date : 2018-07-20
ISBN 10 : 3319182846
Pages : 538 pages
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Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

The Data Science Handbook
Author : Field Cady
Publisher : John Wiley & Sons
Release Date : 2017-02-28
ISBN 10 : 1119092949
Pages : 416 pages
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A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.

Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Author : Patil, Bhushan,Vohra, Manisha
Publisher : IGI Global
Release Date : 2020-10-23
ISBN 10 : 1799830543
Pages : 583 pages
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Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.

Data Analytics in Biomedical Engineering and Healthcare
Author : Kun Chang Lee,Sanjiban Sekhar Roy,Pijush Samui,Vijay Kumar
Publisher : Academic Press
Release Date : 2020-10-23
ISBN 10 : 0128193158
Pages : 292 pages
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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

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches
Author : K. Gayathri Devi,Mamata Rath,Nguyen Thi Dieu Linh
Publisher : CRC Press
Release Date : 2020-10-08
ISBN 10 : 1000179532
Pages : 250 pages
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Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning

Encyclopedic Handbook of Biomaterials and Bioengineering: v. 1-2. Materials
Author : Donald Lee Wise
Publisher : CRC Press
Release Date : 1995
ISBN 10 : 9780824795955
Pages : 1795 pages
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Integrating basic science, engineering, and medical applications, this handbook provides a treatment of materials used in or on the human body - ranging from biopolymers for controlled release drug delivery systems to metal plates used in bone repair and absorbable devices such as sutures.

Handbook of Neuroprosthetic Methods
Author : Warren E. Finn,Peter G. LoPresti
Publisher : CRC Press
Release Date : 2002-12-16
ISBN 10 : 1420040871
Pages : 456 pages
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Work in the field of neuroprosthetics requires multidisciplinary teams, but these collaborators must meet on common ground to develop an understanding of the capabilities and limitations of each part of a bioengineering project. The Handbook of Neuroprosthetic Methods provides a comprehensive resource for the techniques, methodologies, and options available to properly design and undertake experiments within the field of neuroprosthetics. It combines the most commonly employed concepts, applications, and knowledge from the many disciplines associated with neuroprosthetic research to foster more effective, profitable, and productive collaborations. From basic neurophysiology to emerging technologies, this book provides a clear introduction to the entire range of neuroprosthetic systems. Each chapter includes background information, methodology, illustrative figures that clarify experimental methods, and tables that outline and compare experimental choices. The last part of each chapter provides practical applications and examples that relate the topic to the actual design and implementation of a neuroprosthetic system or device. Through its exploration of a variety of developmental processes, the book provides guidance on issues that have yet to be solved, strategies for solving such problems, and the pitfalls often encountered when developing neural prostheses. Whether you are new to or a veteran of the field, whether you work directly or indirectly with neuroprosthesis projects, the Handbook of Neuroprosthetic Methods provides an accessible common ground for all involved in neuroprosthetic design and research.

Environmental Bioengineering
Author : Lawrence K. Wang,Joo-Hwa Tay,Stephen Tiong Lee Tay,Yung-Tse Hung
Publisher : Springer Science & Business Media
Release Date : 2010-06-25
ISBN 10 : 9781603270311
Pages : 867 pages
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The past 30 years have seen the emergence of a growing desire worldwide that positive actions be taken to restore and protect the environment from the degrading effects of all forms of pollution – air, water, soil, and noise. Since pollution is a direct or indirect consequence of waste production, the seemingly idealistic demand for “zero discharge” can be construed as an unrealistic demand for zero waste. However, as long as waste continues to exist, we can only attempt to abate the subsequent pollution by converting it to a less noxious form. Three major questions usually arise when a particular type of pollution has been identi ed: (1) How serious is the pollution? (2) Is the technology to abate it available? and (3) Do the costs of abatement justify the degree of abatement achieved? This book is one of the volumes of the Handbook of Environmental Engineering series. The principal intention of this series is to help readers formulate answers to the above three questions. The traditional approach of applying tried-and-true solutions to speci c pollution problems has been a major contributing factor to the success of environmental engineering, and has accounted in large measure for the establishment of a “methodology of pollution control. ” However, the realization of the ever-increasing complexity and interrelated nature of current environmental problems renders it imperative that intelligent planning of pollution abatement systems be undertaken.

The Physiological Measurement Handbook
Author : John G. Webster
Publisher : CRC Press
Release Date : 2014-12-11
ISBN 10 : 1439808481
Pages : 616 pages
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The Physiological Measurement Handbook presents an extensive range of topics that encompass the subject of measurement in all departments of medicine. The handbook describes the use of instruments and techniques for practical measurements required in medicine. It covers sensors, techniques, hardware, and software as well as information on processing systems, automatic data acquisition, reduction and analysis, and their incorporation for diagnosis. Suitable for both instrumentation designers and users, the handbook enables biomedical engineers, scientists, researchers, students, health care personnel, and those in the medical device industry to explore the different methods available for measuring a particular physiological variable. It helps readers select the most suitable method by comparing alternative methods and their advantages and disadvantages. In addition, the book provides equations for readers focused on discovering applications and solving diagnostic problems arising in medical fields not necessarily in their specialty. It also includes specialized information needed by readers who want to learn advanced applications of the subject, evaluative opinions, and possible areas for future study.

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
Author : Exarchos, Themis P.,Papadopoulos, Athanasios,Fotiadis, Dimitrios I.
Publisher : IGI Global
Release Date : 2009-04-30
ISBN 10 : 1605663158
Pages : 598 pages
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"This book includes state-of-the-art methodologies that introduce biomedical imaging in decision support systems and their applications in clinical practice"--Provided by publisher.

Handbook of Optimization in Medicine
Author : Panos M. Pardalos,H. Edwin Romeijn
Publisher : Springer Science & Business Media
Release Date : 2009-04-05
ISBN 10 : 0387097708
Pages : 442 pages
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Handbook of Optimization in Medicine is devoted to examining the dramatic increase in the application of effective optimization techniques to the delivery of health care. The articles, written by experts, focus on models and algorithms that have led to more efficient and sophisticated treatments of patients. Topics covered include: optimization in medical imaging, classification and data mining with medical applications, treatment of epilepsy and other brain disorders, treatment of head-and-neck, prostate, and other cancers using conventional conformal and intensity-modulated radiation therapy as well as proton therapy, treatment selection for breast cancer based on new classification schemes, optimization for the genome project, optimal timing of organ transplants.