Handbook of Data Science Approaches for Biomedical Engineering Book

Handbook of Data Science Approaches for Biomedical Engineering


  • Author : Valentina Emilia Balas
  • Publisher : Academic Press
  • Release Date : 2019-11-13
  • Genre: Science
  • Pages : 318
  • ISBN 10 : 9780128183199

DOWNLOAD BOOK
Handbook of Data Science Approaches for Biomedical Engineering Excerpt :

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 Book

Data Deduplication Approaches


  • Author : Tin Thein Thwel
  • Publisher : Academic Press
  • Release Date : 2020-11-25
  • Genre: Science
  • Pages : 404
  • ISBN 10 : 9780128236338

DOWNLOAD BOOK
Data Deduplication Approaches Excerpt :

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

Efficient Data Handling for Massive Internet of Medical Things Book

Efficient Data Handling for Massive Internet of Medical Things


  • Author : Chinmay Chakraborty
  • Publisher : Springer Nature
  • Release Date : 2021-09-01
  • Genre: Technology & Engineering
  • Pages : 388
  • ISBN 10 : 9783030666330

DOWNLOAD BOOK
Efficient Data Handling for Massive Internet of Medical Things Excerpt :

This book focuses on recent advances and different research areas in multi-modal data fusion under healthcare informatics and seeks out theoretical, methodological, well-established and validated empirical work dealing with these different topics. This book brings together the latest industrial and academic progress, research, and development efforts within the rapidly maturing health informatics ecosystem. Contributions highlight emerging data fusion topics that support prospective healthcare applications. The book also presents various technologies and concerns regarding energy aware and secure sensors and how they can reduce energy consumption in health care applications. It also discusses the life cycle of sensor devices and protocols with the help of energy-aware design, production, and utilization, as well as the Internet of Things technologies such as tags, sensors, sensing networks, and Internet technologies. In a nutshell, this book gives a comprehensive overview of the state-of-the-art theories and techniques for massive data handling and access in medical data and smart health in IoT, and provides useful guidelines for the design of massive Internet of Medical Things.

Impact of AI and Data Science in Response to Coronavirus Pandemic Book

Impact of AI and Data Science in Response to Coronavirus Pandemic


  • Author : Sushruta Mishra
  • Publisher : Springer Nature
  • Release Date : 2021-07-22
  • Genre: Technology & Engineering
  • Pages : 324
  • ISBN 10 : 9789811627866

DOWNLOAD BOOK
Impact of AI and Data Science in Response to Coronavirus Pandemic Excerpt :

The book presents advanced AI based technologies in dealing with COVID-19 outbreak and provides an in-depth analysis of variety of COVID-19 datasets throughout globe. It discusses recent artificial intelligence based algorithms and models for data analysis of COVID-19 symptoms and its possible remedies. It provides a unique opportunity to present the work on state-of-the-art of modern artificial intelligence tools and technologies to track and forecast COVID-19 cases. It indicates insights and viewpoints from scholars regarding risk and resilience analytics for policy making and operations of large-scale systems on this epidemic. A snapshot of the latest architectures, frameworks in machine learning and data science are also highlighted to gather and aggregate data records related to COVID-19 and to diagnose the virus. It delivers significant research outcomes and inspiring new real-world applications with respect to feasible AI based solutions in COVID-19 outbreak. In addition, it discusses strong preventive measures to control such pandemic.

Big Data Analytics and Computational Intelligence for Cybersecurity Book

Big Data Analytics and Computational Intelligence for Cybersecurity


  • Author : Mariya Ouaissa
  • Publisher : Springer Nature
  • Release Date : 2023-01-27
  • Genre: Big data
  • Pages : 336
  • ISBN 10 : 9783031057526

DOWNLOAD BOOK
Big Data Analytics and Computational Intelligence for Cybersecurity Excerpt :

This book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks.

Demystifying Big Data  Machine Learning  and Deep Learning for Healthcare Analytics Book

Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics


  • Author : Pradeep N
  • Publisher : Academic Press
  • Release Date : 2021-06-25
  • Genre: Science
  • Pages : 372
  • ISBN 10 : 9780128220443

DOWNLOAD BOOK
Demystifying Big Data Machine Learning and Deep Learning for Healthcare Analytics Excerpt :

Demystifying Big Data, Machine Learning, and Deep Learning for Healthcare Analytics presents the changing world of data utilization, especially in clinical healthcare. Various techniques, methodologies, and algorithms are presented in this book to organize data in a structured manner that will assist physicians in the care of patients and help biomedical engineers and computer scientists understand the impact of these techniques on healthcare analytics. The book is divided into two parts: Part 1 covers big data aspects such as healthcare decision support systems and analytics-related topics. Part 2 focuses on the current frameworks and applications of deep learning and machine learning, and provides an outlook on future directions of research and development. The entire book takes a case study approach, providing a wealth of real-world case studies in the application chapters to act as a foundational reference for biomedical engineers, computer scientists, healthcare researchers, and clinicians. Provides a comprehensive reference for biomedical engineers, computer scientists, advanced industry practitioners, researchers, and clinicians to understand and develop healthcare analytics using advanced tools and technologies Includes in-depth illustrations of advanced techniques via dataset samples, statistical tables, and graphs with algorithms and computational methods for developing new applications in healthcare informatics Unique case study approach provides readers with insights for practical clinical implementation

Internet of Things for Healthcare Technologies Book
Score: 5
From 1 Ratings

Internet of Things for Healthcare Technologies


  • Author : Chinmay Chakraborty
  • Publisher : Springer Nature
  • Release Date : 2020-06-08
  • Genre: Technology & Engineering
  • Pages : 324
  • ISBN 10 : 9789811541124

DOWNLOAD BOOK
Internet of Things for Healthcare Technologies Excerpt :

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.

AI Enabled Multiple Criteria Decision Making Approaches for Healthcare Management Book

AI Enabled Multiple Criteria Decision Making Approaches for Healthcare Management


  • Author : Kautish, Sandeep
  • Publisher : IGI Global
  • Release Date : 2022-06-30
  • Genre: Computers
  • Pages : 294
  • ISBN 10 : 9781668444078

DOWNLOAD BOOK
AI Enabled Multiple Criteria Decision Making Approaches for Healthcare Management Excerpt :

Multiple-criteria decision making, including multiple rule-based decision making, multiple-objective decision making, and multiple-attribute decision making, is used by clinical decision makers to analyze healthcare issues from various perspectives. In practical healthcare cases, semi-structured and unstructured decision-making issues involve multiple criteria that may conflict with each other. Thus, the use of multiple-criteria decision making is a promising source of practical solutions for such problems. AI-Enabled Multiple-Criteria Decision-Making Approaches for Healthcare Management investigates the contributions of practical multiple-criteria decision analysis applications and cases for healthcare management. The book also considers the best practices and tactics for utilizing multiple-criteria decision making to ensure the technology is utilized appropriately. Covering key topics such as fuzzy data, augmented reality, blockchain, and data transmission, this reference work is ideal for computer scientists, healthcare professionals, nurses, policymakers, researchers, scholars, academicians, practitioners, educators, and students.

Web Information Systems Engineering     WISE 2020 Book

Web Information Systems Engineering WISE 2020


  • Author : Zhisheng Huang
  • Publisher : Springer Nature
  • Release Date : 2020-10-20
  • Genre: Computers
  • Pages : 610
  • ISBN 10 : 9783030620080

DOWNLOAD BOOK
Web Information Systems Engineering WISE 2020 Excerpt :

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

Artificial Intelligence Techniques in IoT Sensor Networks Book

Artificial Intelligence Techniques in IoT Sensor Networks


  • Author : Mohamed Elhoseny
  • Publisher : CRC Press
  • Release Date : 2020-12-18
  • Genre: Computers
  • Pages : 221
  • ISBN 10 : 9781000318708

DOWNLOAD BOOK
Artificial Intelligence Techniques in IoT Sensor Networks Excerpt :

Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks. This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master’s students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications. This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.

Green Computing and Predictive Analytics for Healthcare Book

Green Computing and Predictive Analytics for Healthcare


  • Author : Sourav Banerjee
  • Publisher : CRC Press
  • Release Date : 2020-12-10
  • Genre: Computers
  • Pages : 190
  • ISBN 10 : 9781000223941

DOWNLOAD BOOK
Green Computing and Predictive Analytics for Healthcare Excerpt :

Green Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government En

Privacy and Security Issues in Big Data Book

Privacy and Security Issues in Big Data


  • Author : Pradip Kumar Das
  • Publisher : Springer Nature
  • Release Date : 2021-04-23
  • Genre: Computers
  • Pages : 211
  • ISBN 10 : 9789811610073

DOWNLOAD BOOK
Privacy and Security Issues in Big Data Excerpt :

This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data. It focuses on the results obtained after applying a systematic mapping study and implementation of security in the big data for utilizing in business under the establishment of “Business Intelligence”. The chapters start with the definition of big data, discussions why security is used in business infrastructure and how the security can be improved. In this book, some of the data security and data protection techniques are focused and it presents the challenges and suggestions to meet the requirements of computing, communication and storage capabilities for data mining and analytics applications with large aggregate data in business.

Internet of Things Based Smart Healthcare Book

Internet of Things Based Smart Healthcare


  • Author : Suparna Biswas
  • Publisher : Springer Nature
  • Release Date : 2022
  • Genre: Electronic books
  • Pages : 394
  • ISBN 10 : 9789811914089

DOWNLOAD BOOK
Internet of Things Based Smart Healthcare Excerpt :

This book provides both the developers and the users with an awareness of the challenges and opportunities of advancements in healthcare paradigm with the application and availability of advanced hardware, software, tools, technique or algorithm development stemming the Internet of Things. The book helps readers to bridge the gap in their three understanding of three major domains and their interconnections: Hardware tested and software APP development for data collection, intelligent protocols for analysis and knowledge extraction. Medical expertise to interpret extracted knowledge towards disease prediction or diagnosis and support. Security experts to ensure data correctness for precise advice. The book provides state-of-the-art overviews by active researchers, technically elaborating healthcare architectures/frameworks, protocols, algorithms, methodologies followed by experimental results and evaluation. Future direction and scope will be precisely documented for interested readers.

Big Data Analysis for Green Computing Book

Big Data Analysis for Green Computing


  • Author : Rohit Sharma
  • Publisher : CRC Press
  • Release Date : 2021-10-29
  • Genre: Computers
  • Pages : 186
  • ISBN 10 : 9781000481778

DOWNLOAD BOOK
Big Data Analysis for Green Computing Excerpt :

This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

Augmented Intelligence in Healthcare  A Pragmatic and Integrated Analysis Book

Augmented Intelligence in Healthcare A Pragmatic and Integrated Analysis


  • Author : Sushruta Mishra
  • Publisher : Springer Nature
  • Release Date : 2023-01-27
  • Genre: Artificial intelligence
  • Pages : 503
  • ISBN 10 : 9789811910760

DOWNLOAD BOOK
Augmented Intelligence in Healthcare A Pragmatic and Integrated Analysis Excerpt :

The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.