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Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
A Book

by Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Manju Khari

  • Publisher : Academic Press
  • Release : 2019-11-13
  • Pages : 318
  • ISBN : 0128183195
  • Language : En, Es, Fr & De
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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

Data Deduplication Approaches
Concepts, Strategies, and Challenges

by Tin Thein Thwel,G. R. Sinha

  • Publisher : Academic Press
  • Release : 2020-11-25
  • Pages : 404
  • ISBN : 0128236337
  • Language : En, Es, Fr & De
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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

Internet of Things for Healthcare Technologies
A Book

by Chinmay Chakraborty,Amit Banerjee,Maheshkumar H. Kolekar,Lalit Garg,Basabi Chakraborty

  • Publisher : Springer Nature
  • Release : 2020-06-08
  • Pages : 324
  • ISBN : 9811541124
  • Language : En, Es, Fr & De
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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.

Handbook of Artificial Intelligence in Biomedical Engineering

Handbook of Artificial Intelligence in Biomedical Engineering
A Book

by Krishnan Saravanan,Ramesh Kesavan,B. Surendiran,G. S. Mahalakshmi

  • Publisher : Unknown Publisher
  • Release : 2021
  • Pages : 538
  • ISBN : 9781003045564
  • Language : En, Es, Fr & De
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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. Topics include: Security and privacy issues in biomedical AI systems and potential solutions Healthcare applications using biomedical AI systems Machine learning in biomedical engineering Live patient monitoring systems Semantic annotation of healthcare data This book presents a broad exploration of biomedical systems using artificial intelligence techniques with detailed coverage of the applications, techniques, algorithms, platforms, and tools in biomedical AI systems. This book will benefit researchers, medical and industry practitioners, academicians, and students"--

Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science

Handbook of Research on Cloud and Fog Computing Infrastructures for Data Science
A Book

by Raj, Pethuru,Raman, Anupama

  • Publisher : IGI Global
  • Release : 2018-05-18
  • Pages : 440
  • ISBN : 1522559736
  • Language : En, Es, Fr & De
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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 Deep Learning in Biomedical Engineering

Handbook of Deep Learning in Biomedical Engineering
Techniques and Applications

by Valentina Emilia Balas,Brojo Kishore Mishra,Raghvendra Kumar

  • Publisher : Academic Press
  • Release : 2020-11-23
  • Pages : 320
  • ISBN : 0128230479
  • Language : En, Es, Fr & De
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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 Research on Data Science for Effective Healthcare Practice and Administration

Handbook of Research on Data Science for Effective Healthcare Practice and Administration
A Book

by Noughabi, Elham Akhond Zadeh,Raahemi, Bijan,Albadvi, Amir,Far, Behrouz H.

  • Publisher : IGI Global
  • Release : 2017-07-20
  • Pages : 545
  • ISBN : 1522525165
  • Language : En, Es, Fr & De
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Data science has always been an effective way of extracting knowledge and insights from information in various forms. One industry that can utilize the benefits from the advances in data science is the healthcare field. The Handbook of Research on Data Science for Effective Healthcare Practice and Administration is a critical reference source that overviews the state of data analysis as it relates to current practices in the health sciences field. Covering innovative topics such as linear programming, simulation modeling, network theory, and predictive analytics, this publication is recommended for all healthcare professionals, graduate students, engineers, and researchers that are seeking to expand their knowledge of efficient techniques for information analysis in the healthcare professions.

Handbook of Big Data Analytics

Handbook of Big Data Analytics
A Book

by Wolfgang Karl Härdle,Henry Horng-Shing Lu,Xiaotong Shen

  • Publisher : Springer
  • Release : 2018-07-20
  • Pages : 538
  • ISBN : 3319182846
  • Language : En, Es, Fr & De
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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.

Targeted Learning in Data Science

Targeted Learning in Data Science
Causal Inference for Complex Longitudinal Studies

by Mark J. van der Laan,Sherri Rose

  • Publisher : Springer
  • Release : 2018-03-28
  • Pages : 640
  • ISBN : 3319653040
  • Language : En, Es, Fr & De
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This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.

Handbook of Neuroimaging Data Analysis

Handbook of Neuroimaging Data Analysis
A Book

by Hernando Ombao,Martin Lindquist,Wesley Thompson,John Aston

  • Publisher : CRC Press
  • Release : 2016-11-18
  • Pages : 662
  • ISBN : 1482220989
  • Language : En, Es, Fr & De
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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

Biomedical Engineering Handbook 2
A Book

by Joseph D. Bronzino

  • Publisher : Springer Science & Business Media
  • Release : 2000-02-15
  • Pages : 329
  • ISBN : 9783540668084
  • Language : En, Es, Fr & De
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Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques
Algorithms, Methods, and Techniques

by Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚

  • Publisher : IGI Global
  • Release : 2009-08-31
  • Pages : 852
  • ISBN : 1605667676
  • Language : En, Es, Fr & De
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"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

A Handbook of Internet of Things in Biomedical and Cyber Physical System

A Handbook of Internet of Things in Biomedical and Cyber Physical System
A Book

by Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Md. Atiqur Rahman Ahad

  • Publisher : Springer
  • Release : 2019-07-16
  • Pages : 314
  • ISBN : 3030239837
  • Language : En, Es, Fr & De
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This book presents a compilation of state-of-the-art work on biomedical and cyber-physical systems in connection with the Internet of Things, and successfully blends theory and practice. The book covers the studies belonging to Biomedical and Cyber-physical System, so it is a unique effort by the research experts, who are divulging in the domain deeply. The book is very easy for the audience, who are doing study in the Biomedical and Cyber-physical System; it helps to read some real-time scenarios from where the reader in general gets many sparking ideas to convert it into the research problems in their studies. This book is of use to solve down the problems of graduate, postgraduate, doctoral industry executives, who are involving in the cutting-edge work of Internet of Things with Biomedical or Cyber-physical System, with the help of real-time solutions, given in the formation of chapters by subject’s experts. The key uses of this book are in the area of Internet of Things in connection with Cyber-physical System as well as Biomedical domain.

Environmental Bioengineering

Environmental Bioengineering
A Book

by Lawrence K. Wang,Joo-Hwa Tay,Stephen Tiong Lee Tay,Yung-Tse Hung

  • Publisher : Springer Science & Business Media
  • Release : 2010-06-25
  • Pages : 867
  • ISBN : 9781603270311
  • Language : En, Es, Fr & De
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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.

CRC Critical Reviews in Bioengineering

CRC Critical Reviews in Bioengineering
A Book

by Chemical Rubber Company

  • Publisher : Unknown Publisher
  • Release : 1981
  • Pages : 329
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Encyclopedic Handbook of Biomaterials and Bioengineering: v. 1-2. Materials

Encyclopedic Handbook of Biomaterials and Bioengineering: v. 1-2. Materials
A Book

by Donald Lee Wise

  • Publisher : CRC Press
  • Release : 1995
  • Pages : 1795
  • ISBN : 9780824795955
  • Language : En, Es, Fr & De
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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.

The Physiological Measurement Handbook

The Physiological Measurement Handbook
A Book

by John G. Webster

  • Publisher : CRC Press
  • Release : 2014-12-11
  • Pages : 616
  • ISBN : 1439808481
  • Language : En, Es, Fr & De
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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.

Instrumentation Handbook for Biomedical Engineers

Instrumentation Handbook for Biomedical Engineers
A Book

by Mesut Sahin

  • Publisher : CRC Press
  • Release : 2020-10-27
  • Pages : 168
  • ISBN : 1466504846
  • Language : En, Es, Fr & De
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The book fills a void as a textbook with hands-on laboratory exercises designed for biomedical engineering undergraduates in their senior year or the first year of graduate studies specializing in electrical aspects of bioinstrumentation. Each laboratory exercise concentrates on measuring a biophysical or biomedical entity, such as force, blood pressure, temperature, heart rate, respiratory rate, etc., and guides students though all the way from sensor level to data acquisition and analysis on the computer. The book distinguishes itself from others by providing electrical circuits and other measurement setups that have been tested by the authors while teaching undergraduate classes at their home institute over many years. Key Features: • Hands-on laboratory exercises on measurements of biophysical and biomedical variables • Each laboratory exercise is complete by itself and they can be covered in any sequence desired by the instructor during the semester • Electronic equipment and supplies required are typical for biomedical engineering departments • Data collected by undergraduate students and data analysis results are provided as samples • Additional information and references are included for preparing a report or further reading at the end of each chapter Students using this book are expected to have basic knowledge of electrical circuits and troubleshooting. Practical information on circuit components, basic laboratory equipment, and circuit troubleshooting is also provided in the first chapter of the book.

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
A Book

by Exarchos, Themis P.,Papadopoulos, Athanasios,Fotiadis, Dimitrios I.

  • Publisher : IGI Global
  • Release : 2009-04-30
  • Pages : 598
  • ISBN : 1605663158
  • Language : En, Es, Fr & De
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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

Handbook of Optimization in Medicine
A Book

by Panos M. Pardalos,H. Edwin Romeijn

  • Publisher : Springer Science & Business Media
  • Release : 2009-04-05
  • Pages : 442
  • ISBN : 0387097708
  • Language : En, Es, Fr & De
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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.