Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
PDF
  • eBook:
    Handbook of Data Science Approaches for Biomedical Engineering
  • Author:
    Valentina E. Balas, Vijender Kumar Solanki, Raghvendra Kumar, Manju Khari
  • Edition:
    1 edition
  • Categories:
  • Data:
    November 27, 2019
  • ISBN:
    0128183187
  • ISBN-13:
    9780128183182
  • Language:
    English
  • Pages:
    318 pages
  • Format:
    PDF

Book Description
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.

Content

Chapter 1: Analysis of the role and scope of big data analytics with loT in health care domain
Chapter 2: Automated human cortical bone Haversian canal histomorphometric comparison system
Chapter 3: Biomedical instrument and automation: automatic instrumentation in biomedical engineering
Chapter 4: Performance improvement in contemporary health care using loT allied with big data
Chapter 5: Emerging trends in loT and big data analytics for biomedical and health care technologies
Chapter 6: Recent advances on big data analysis for malaria prediction and various diagnosis methodologies
Chapter 7: Semantic interoperability in 10 T and big data for health care: a collaborative approach
Chapter 8: Why big data, and what it is: basics to advanced big data journey for the medical industry
Chapter 9: Semisupervised fuzzy clustering methods for X-ray image segmentation

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