Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
Author: Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Manju Khari
Publsiher: Academic Press
Total Pages: 318
Release: 2019-11-13
ISBN 10: 0128183195
ISBN 13: 9780128183199
Language: EN, FR, DE, ES & NL

Handbook of Data Science Approaches for Biomedical Engineering Book Review:

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

Handbook of Artificial Intelligence in Biomedical Engineering

Handbook of Artificial Intelligence in Biomedical Engineering
Author: Saravanan Krishnan,Ramesh Kesavan,B. Surendiran,G.S. Mahalakshmi
Publsiher: CRC Press
Total Pages: 538
Release: 2021-03-30
ISBN 10: 100006767X
ISBN 13: 9781000067675
Language: EN, FR, DE, ES & NL

Handbook of Artificial Intelligence in Biomedical Engineering Book Review:

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 Deep Learning in Biomedical Engineering

Handbook of Deep Learning in Biomedical Engineering
Author: Valentina Emilia Balas,Brojo Kishore Mishra,Raghvendra Kumar
Publsiher: Academic Press
Total Pages: 320
Release: 2020-11-23
ISBN 10: 0128230479
ISBN 13: 9780128230473
Language: EN, FR, DE, ES & NL

Handbook of Deep Learning in Biomedical Engineering Book Review:

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. ~

Data Deduplication Approaches

Data Deduplication Approaches
Author: Tin Thein Thwel,G. R. Sinha
Publsiher: Academic Press
Total Pages: 404
Release: 2020-11-25
ISBN 10: 0128236337
ISBN 13: 9780128236338
Language: EN, FR, DE, ES & NL

Data Deduplication Approaches Book Review:

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

The Data Science Handbook

The Data Science Handbook
Author: Field Cady
Publsiher: John Wiley & Sons
Total Pages: 416
Release: 2017-02-28
ISBN 10: 1119092949
ISBN 13: 9781119092940
Language: EN, FR, DE, ES & NL

The Data Science Handbook Book Review:

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 Neuroimaging Data Analysis

Handbook of Neuroimaging Data Analysis
Author: Hernando Ombao,Martin Lindquist,Wesley Thompson,John Aston
Publsiher: CRC Press
Total Pages: 662
Release: 2016-11-18
ISBN 10: 1482220989
ISBN 13: 9781482220988
Language: EN, FR, DE, ES & NL

Handbook of Neuroimaging Data Analysis Book Review:

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.

Handbook of Research on Engineering Business and Healthcare Applications of Data Science and Analytics

Handbook of Research on Engineering  Business  and Healthcare Applications of Data Science and Analytics
Author: Patil, Bhushan,Vohra, Manisha
Publsiher: IGI Global
Total Pages: 583
Release: 2020-10-23
ISBN 10: 1799830543
ISBN 13: 9781799830542
Language: EN, FR, DE, ES & NL

Handbook of Research on Engineering Business and Healthcare Applications of Data Science and Analytics Book Review:

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.

Handbook of Research on Blockchain Technology

Handbook of Research on Blockchain Technology
Author: Saravanan Krishnan,Valentina E. Balas,Julie Golden,Y. Harold Robinson,S. Balaji,Raghvendra Kumar
Publsiher: Academic Press
Total Pages: 476
Release: 2020-02-04
ISBN 10: 012820415X
ISBN 13: 9780128204153
Language: EN, FR, DE, ES & NL

Handbook of Research on Blockchain Technology Book Review:

Handbook of Research on Blockchain Technology presents the latest information on the adaptation and implementation of Blockchain technologies in real world business, scientific, healthcare and biomedical applications. The book's editors present the rapid advancements in existing business models by applying Blockchain techniques. Novel architectural solutions in the deployment of Blockchain comprise the core aspects of this book. Several use cases with IoT, biomedical engineering, and smart cities are also incorporated. As Blockchain is a relatively new technology that exploits decentralized networks and is used in many sectors for reliable, cost-effective and rapid business transactions, this book is a welcomed addition on existing knowledge. Financial services, retail, insurance, logistics, supply chain, public sectors and biomedical industries are now investing in Blockchain research and technologies for their business growth. Blockchain prevents double spending in financial transactions without the need of a trusted authority or central server. It is a decentralized ledger platform that facilitates verifiable transactions between parties in a secure and smart way. Presents the evolution of blockchain, from fundamental theories, to present forms Explains the concepts of blockchain related to cloud/edge computing, smart healthcare, smart cities and Internet of Things (IoT) Provides complete coverage of the various tools, platforms and techniques used in blockchain Explores smart contract tools and consensus algorithms Covers a variety of applications with real world case studies in areas such as biomedical engineering, supply chain management, and tracking of goods and delivery

Instrumentation Handbook for Biomedical Engineers

Instrumentation Handbook for Biomedical Engineers
Author: Mesut Sahin
Publsiher: CRC Press
Total Pages: 168
Release: 2020-10-27
ISBN 10: 1466504846
ISBN 13: 9781466504844
Language: EN, FR, DE, ES & NL

Instrumentation Handbook for Biomedical Engineers Book Review:

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 Biomedical Image Analysis

Handbook of Biomedical Image Analysis
Author: David Wilson,Swamy Laxminarayan
Publsiher: Springer Science & Business Media
Total Pages: 574
Release: 2007-04-25
ISBN 10: 0306486083
ISBN 13: 9780306486081
Language: EN, FR, DE, ES & NL

Handbook of Biomedical Image Analysis Book Review:

Our goal is to develop automated methods for the segmentation of thr- dimensional biomedical images. Here, we describe the segmentation of c- focal microscopy images of bee brains (20 individuals) by registration to one or several atlas images. Registration is performed by a highly parallel imp- mentation of an entropy-based nonrigid registration algorithm using B-spline transformations. We present and evaluate different methods to solve the cor- spondence problem in atlas based registration. An image can be segmented by registering it to an individual atlas, an average atlas, or multiple atlases. When registering to multiple atlases, combining the individual segmentations into a ?nalsegmentationcanbeachievedbyatlasselection,ormulticlassi?erdecision fusion. Wedescribeallthesemethodsandevaluatethesegmentationaccuracies that they achieve by performing experiments with electronic phantoms as well as by comparing their outputs to a manual gold standard. The present work is focused on the mathematical and computational t- ory behind a technique for deformable image registration termed Hyperelastic Warping, and demonstration of the technique via applications in image regist- tion and strain measurement. The approach combines well-established prin- ples of nonlinear continuum mechanics with forces derived directly from thr- dimensional image data to achieve registration. The general approach does not require the de?nition of landmarks, ?ducials, or surfaces, although it can - commodate these if available. Representative problems demonstrate the robust and ?exible nature of the approach. Three-dimensional registration methods are introduced for registering MRI volumes of the pelvis and prostate. The chapter ?rst reviews the applications, xi xii Preface challenges, and previous methods of image registration in the prostate.

Handbook of Big Data Analytics

Handbook of Big Data Analytics
Author: Wolfgang Karl Härdle,Henry Horng-Shing Lu,Xiaotong Shen
Publsiher: Springer
Total Pages: 538
Release: 2018-07-20
ISBN 10: 3319182846
ISBN 13: 9783319182841
Language: EN, FR, DE, ES & NL

Handbook of Big Data Analytics Book Review:

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.

Computational Intelligence and Its Applications in Healthcare

Computational Intelligence and Its Applications in Healthcare
Author: Prashant Johri,Jitendra Kumar Verma,Sudip Paul
Publsiher: Academic Press
Total Pages: 264
Release: 2020-08-01
ISBN 10: 0128206195
ISBN 13: 9780128206195
Language: EN, FR, DE, ES & NL

Computational Intelligence and Its Applications in Healthcare Book Review:

Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. Provides coverage of fuzzy logic, neural networks, evolutionary computation, learning theory, probabilistic methods, telemedicine, and robotics applications Includes coverage of artificial intelligence and biological applications, soft computing, image and signal processing, and genetic algorithms Presents the latest developments in computational methods in healthcare Bridges the gap between obsolete literature and current literature

Intelligent Data Analysis for Biomedical Applications

Intelligent Data Analysis for Biomedical Applications
Author: Hemanth D. Jude,Deepak Gupta,Valentina Emilia Balas
Publsiher: Academic Press
Total Pages: 294
Release: 2019-03-15
ISBN 10: 0128156430
ISBN 13: 9780128156438
Language: EN, FR, DE, ES & NL

Intelligent Data Analysis for Biomedical Applications Book Review:

Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases. Provides the methods and tools necessary for intelligent data analysis and gives solutions to problems resulting from automated data collection Contains an analysis of medical databases to provide diagnostic expert systems Addresses the integration of intelligent data analysis techniques within biomedical information systems

Handbook of Medical Image Computing and Computer Assisted Intervention

Handbook of Medical Image Computing and Computer Assisted Intervention
Author: S. Kevin Zhou,Daniel Rueckert,Gabor Fichtinger
Publsiher: Academic Press
Total Pages: 1072
Release: 2019-10-18
ISBN 10: 0128165863
ISBN 13: 9780128165867
Language: EN, FR, DE, ES & NL

Handbook of Medical Image Computing and Computer Assisted Intervention Book Review:

Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications. This book is written primarily for university researchers, graduate students and professional practitioners (assuming an elementary level of linear algebra, probability and statistics, and signal processing) working on medical image computing and computer assisted intervention. Presents the key research challenges in medical image computing and computer-assisted intervention Written by leading authorities of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society Contains state-of-the-art technical approaches to key challenges Demonstrates proven algorithms for a whole range of essential medical imaging applications Includes source codes for use in a plug-and-play manner Embraces future directions in the fields of medical image computing and computer-assisted intervention

Internet of Things in Biomedical Engineering

Internet of Things in Biomedical Engineering
Author: Valentina E. Balas,Le Hoang Son,Sudan Jha,Manju Khari,Raghvendra Kumar
Publsiher: Academic Press
Total Pages: 379
Release: 2019-06-14
ISBN 10: 0128173572
ISBN 13: 9780128173572
Language: EN, FR, DE, ES & NL

Internet of Things in Biomedical Engineering Book Review:

Internet of Things in Biomedical Engineering presents the most current research in Internet of Things (IoT) applications for clinical patient monitoring and treatment. The book takes a systems-level approach for both human-factors and the technical aspects of networking, databases and privacy. Sections delve into the latest advances and cutting-edge technologies, starting with an overview of the Internet of Things and biomedical engineering, as well as a focus on ‘daily life.’ Contributors from various experts then discuss ‘computer assisted anthropology,’ CLOUDFALL, and image guided surgery, as well as bio-informatics and data mining. This comprehensive coverage of the industry and technology is a perfect resource for students and researchers interested in the topic. Presents recent advances in IoT for biomedical engineering, covering biometrics, bioinformatics, artificial intelligence, computer vision and various network applications Discusses big data and data mining in healthcare and other IoT based biomedical data analysis Includes discussions on a variety of IoT applications and medical information systems Includes case studies and applications, as well as examples on how to automate data analysis with Perl R in IoT

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
Author: Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚
Publsiher: IGI Global
Total Pages: 852
Release: 2009-08-31
ISBN 10: 1605667676
ISBN 13: 9781605667676
Language: EN, FR, DE, ES & NL

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

"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.

Soft Methods for Data Science

Soft Methods for Data Science
Author: Maria Brigida Ferraro,Paolo Giordani,Barbara Vantaggi,Marek Gagolewski,María Ángeles Gil,Przemysław Grzegorzewski,Olgierd Hryniewicz
Publsiher: Springer
Total Pages: 535
Release: 2016-08-30
ISBN 10: 3319429728
ISBN 13: 9783319429724
Language: EN, FR, DE, ES & NL

Soft Methods for Data Science Book Review:

This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science.

Targeted Learning in Data Science

Targeted Learning in Data Science
Author: Mark J. van der Laan,Sherri Rose
Publsiher: Springer
Total Pages: 640
Release: 2018-03-28
ISBN 10: 3319653040
ISBN 13: 9783319653044
Language: EN, FR, DE, ES & NL

Targeted Learning in Data Science Book Review:

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.

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

A Handbook of Internet of Things in Biomedical and Cyber Physical System
Author: Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Md. Atiqur Rahman Ahad
Publsiher: Springer
Total Pages: 314
Release: 2019-07-16
ISBN 10: 3030239837
ISBN 13: 9783030239831
Language: EN, FR, DE, ES & NL

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

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.

CRC Critical Reviews in Bioengineering

CRC Critical Reviews in Bioengineering
Author: Chemical Rubber Company
Publsiher: Unknown
Total Pages: 329
Release: 1981
ISBN 10:
ISBN 13: UCAL:B4332902
Language: EN, FR, DE, ES & NL

CRC Critical Reviews in Bioengineering Book Review: