Data Analytics in Biomedical Engineering and Healthcare Book

Data Analytics in Biomedical Engineering and Healthcare


  • Author : Kun Chang Lee
  • Publisher : Academic Press
  • Release Date : 2020-10-18
  • Genre: Science
  • Pages : 292
  • ISBN 10 : 9780128193150
  • Total Read : 98
  • File Size : 18,5 Mb

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Data Analytics in Biomedical Engineering and Healthcare Summary:

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

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
  • Total Read : 97
  • File Size : 12,9 Mb

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Handbook of Data Science Approaches for Biomedical Engineering Summary:

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 Analytics in Biomedical Engineering and Healthcare Book

Data Analytics in Biomedical Engineering and Healthcare


  • Author : Kun Chang Lee
  • Publisher : Academic Press
  • Release Date : 2020-10-30
  • Genre: Science
  • Pages : 296
  • ISBN 10 : 9780128193143
  • Total Read : 96
  • File Size : 7,6 Mb

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Data Analytics in Biomedical Engineering and Healthcare Summary:

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

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare Book

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare


  • Author : Janmenjoy Nayak
  • Publisher : Academic Press
  • Release Date : 2021-04-08
  • Genre: Science
  • Pages : 396
  • ISBN 10 : 9780128222614
  • Total Read : 91
  • File Size : 12,6 Mb

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Handbook of Computational Intelligence in Biomedical Engineering and Healthcare Summary:

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important biomedical engineering applications, including biosensors, enzyme immobilization techniques, immuno-assays, and nanomaterials for biosensors and other biomedical techniques. Other sections cover gene-based solutions and applications through computational intelligence techniques and the impact of nonlinear/unstructured data on experimental analysis. Presents a comprehensive handbook that covers an Introduction to Computational Intelligence in Biomedical Engineering and Healthcare, Computational Intelligence Techniques, and Advanced and Emerging Techniques in Computational Intelligence Helps readers analyze and do advanced research in specialty healthcare applications Includes links to websites, videos, articles and other online content to expand and support primary learning objectives

Data Science and Predictive Analytics Book

Data Science and Predictive Analytics


  • Author : Ivo D. Dinov
  • Publisher : Springer
  • Release Date : 2018-08-27
  • Genre: Computers
  • Pages : 832
  • ISBN 10 : 9783319723471
  • Total Read : 92
  • File Size : 9,5 Mb

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Data Science and Predictive Analytics Summary:

Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities. They have led to striking technological advances, affecting all human experiences. Our ability to manage, understand, interrogate, and interpret such extremely large, multisource, heterogeneous, incomplete, multiscale, and incongruent data has not kept pace with the rapid increase of the volume, complexity and proliferation of the deluge of digital information. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder’s law > Moore’s law). Second, traditional discipline-bounds inhibit expeditious progress. Third, our education and training activities have fallen behind the accelerated trend of scientific, information, and communication advances. There are very few rigorous instructional resources, interactive learning materials, and dynamic training environments that support active data science learning. The textbook balances the mathematical foundations with dexterous demonstrations and examples of data, tools, modules and workflows that serve as pillars for the urgently needed bridge to close that supply and demand predictive analytic skills gap. Exposing the enormous opportunities presented by the tsunami of Big data, this textbook aims to identify specific knowledge gaps, educational barriers, and workforce readiness deficiencies. Specifically, it focuses on the development of a transdisciplinary curriculum integrating modern computational methods, advanced data science techniques, innovative biomedical applications, and impactful health analytics. The content of this graduate-level textbook fills a substantial gap in integrating modern engineering concepts, computational algorithms, mathematical optimization, statistical computing and biomedical inference. Big data analytic techniques and predictive scientific methods demand

Big Data Analytics in Bioinformatics and Healthcare Book

Big Data Analytics in Bioinformatics and Healthcare


  • Author : Wang, Baoying
  • Publisher : IGI Global
  • Release Date : 2014-10-31
  • Genre: Computers
  • Pages : 528
  • ISBN 10 : 9781466666122
  • Total Read : 89
  • File Size : 6,5 Mb

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Big Data Analytics in Bioinformatics and Healthcare Summary:

As technology evolves and electronic data becomes more complex, digital medical record management and analysis becomes a challenge. In order to discover patterns and make relevant predictions based on large data sets, researchers and medical professionals must find new methods to analyze and extract relevant health information. Big Data Analytics in Bioinformatics and Healthcare merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management. Complete with interdisciplinary research resources, this publication is an essential reference source for researchers, practitioners, and students interested in the fields of biological computation, database management, and health information technology, with a special focus on the methodologies and tools to manage massive and complex electronic information.

Terahertz Biomedical and Healthcare Technologies Book

Terahertz Biomedical and Healthcare Technologies


  • Author : Amit Banerjee
  • Publisher : Elsevier
  • Release Date : 2020-08-11
  • Genre: Technology & Engineering
  • Pages : 262
  • ISBN 10 : 9780128185575
  • Total Read : 60
  • File Size : 16,7 Mb

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Terahertz Biomedical and Healthcare Technologies Summary:

Terahertz Biomedical and Healthcare Technologies: Materials to Devices reviews emerging advances in terahertz biomedical and healthcare technologies, including advances in fundamental materials science research, device design and fabrication, applications, and challenges and opportunities for improved performance. In addition, the improvement of materials, optical elements, and measuring techniques are also explored. Other sections cover the design and development of wide bandgap semiconductors for terahertz device applications, including their physics, device modeling, characterization and fabrication concepts. Finally, the book touches on potential defense, medical imaging, internet of things, and the machine learning applications of terahertz technologies. Reviews the latest advances in the fundamental and applied research of terahertz technologies, covering key topics in materials science, biomedical engineering and healthcare informatics Includes applications of terahertz technologies in medical imaging, diagnosis and treatment Provides readers with an understanding of the machine learning, pattern recognition, and data analytics research utilized to enhance the effectiveness of terahertz technologies

Data Analytics in Medicine  Concepts  Methodologies  Tools  and Applications Book

Data Analytics in Medicine Concepts Methodologies Tools and Applications


  • Author : Management Association, Information Resources
  • Publisher : IGI Global
  • Release Date : 2019-12-06
  • Genre: Medical
  • Pages : 2071
  • ISBN 10 : 9781799812050
  • Total Read : 78
  • File Size : 9,9 Mb

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Data Analytics in Medicine Concepts Methodologies Tools and Applications Summary:

Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.