Machine Learning, Big Data, and IoT for Medical Informatics

Machine Learning, Big Data, and IoT for Medical Informatics book cover

Machine Learning, Big Data, and IoT for Medical Informatics

Author(s): Pardeep Kumar (Editor), Yugal Kumar (Editor), Mohamed A. Tawhid (Editor), Fatos Xhafa (Series Editor)

  • Publisher: Academic Press
  • Publication Date: 24 Jun. 2021
  • Language: English
  • Print length: 458 pages
  • ISBN-10: 0128217774
  • ISBN-13: 9780128217771

Book Description

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics.

In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data.

This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.

  • Explains the uses of CNN, Deep Learning and extreme machine learning concepts for the design and development of predictive diagnostic systems.
  • Includes several privacy preservation techniques for medical data.
  • Presents the integration of Internet of Things with predictive diagnostic systems for disease diagnosis.
  • Offers case studies and applications relating to machine learning, big data, and health care analysis.

Editorial Reviews

Review

Provides a thorough accounting of semantic information and structure of data with simple and straightforward examples.

From the Back Cover

Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics.

In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data.

This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.

View on Amazon

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