Editors:
- 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)
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Front Matter
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Deep Learning for Biomedical Engineering and Health Informatics
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Front Matter
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Deep Learning and Electronics Health Records
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Front Matter
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Deep Learning for Medical Image Processing
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Front Matter
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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
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Department of Computer Science, North Orissa University, Takatpur, India
Sujata Dash
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School of Computer Science and Engineering, KIIT Deemed to University, Bhubaneswar, India
Biswa Ranjan Acharya
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Computer Science and Engineering Department, G. B. Pant Government Engineering College, New Delhi, India
Mamta Mittal
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Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, USA
Ajith Abraham
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Department of Organizational Systems and Adult Health, University of Maryland, Baltimore, USA
Arpad Kelemen
Bibliographic Information
Book Title: Deep Learning Techniques for Biomedical and Health Informatics
Editors: Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen
Series Title: Studies in Big Data
DOI: https://doi.org/10.1007/978-3-030-33966-1
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-33965-4Published: 25 November 2019
Softcover ISBN: 978-3-030-33968-5Published: 25 November 2020
eBook ISBN: 978-3-030-33966-1Published: 14 November 2019
Series ISSN: 2197-6503
Series E-ISSN: 2197-6511
Edition Number: 1
Number of Pages: XXV, 383
Topics: Computational Intelligence, Data Engineering, Biomedical Engineering and Bioengineering, Big Data, Artificial Intelligence