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Deep Learning Techniques for Biomedical and Health Informatics

  • Book
  • © 2020

Overview

  • Presents state-of-the-art approaches for deep-learning-based biomedical and health-related applications
  • Discusses the latest advances and developments in the fields of biomedical, health informatics, and deep learning
  • Written by experts in the field

Part of the book series: Studies in Big Data (SBD, volume 68)

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Table of contents (16 chapters)

  1. Deep Learning for Biomedical Engineering and Health Informatics

  2. Deep Learning and Electronics Health Records

  3. Deep Learning for Medical Image Processing

Keywords

About this book

This book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model.

This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health.

It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields.

 

Editors and Affiliations

  • Department of Computer Science, North Orissa University, Takatpur, India

    Sujata Dash

  • School of Computer Science and Engineering, KIIT Deemed to University, Bhubaneswar, India

    Biswa Ranjan Acharya

  • Computer Science and Engineering Department, G. B. Pant Government Engineering College, New Delhi, India

    Mamta Mittal

  • Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, USA

    Ajith Abraham

  • Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, USA

    Arpad Kelemen

Bibliographic Information

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