Deep Learning Techniques for Biomedical and Health Informatics

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  • Author : Sujata Dash
  • Publisher : Springer
  • Pages : 383 pages
  • ISBN : 9783030339654
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Deep Learning Techniques for Biomedical and Health Informatics

Download or Read online Deep Learning Techniques for Biomedical and Health Informatics full in PDF, ePub and kindle. this book written by Sujata Dash and published by Springer which was released on 25 November 2019 with total page 383 pages. We cannot guarantee that Deep Learning Techniques for Biomedical and Health Informatics book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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.

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
  • Author : Sujata Dash,Biswa Ranjan Acharya,Mamta Mittal,Ajith Abraham,Arpad Kelemen
  • Publisher : Springer
  • Release : 25 November 2019
GET THIS BOOK Deep Learning Techniques for Biomedical and Health Informatics

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

Deep Learning in Biomedical and Health Informatics

Deep Learning in Biomedical and Health Informatics
  • Author : M. A. Jabbar,Ajith Abraham,Onur Dogan,Ana Maria Madureira,Sanju Tiwari
  • Publisher : CRC Press
  • Release : 26 September 2021
GET THIS BOOK Deep Learning in Biomedical and Health Informatics

This book provides a proficient guide on the relationship between Artificial Intelligence (AI) and healthcare and how AI is changing all aspects of the healthcare industry. It also covers how deep learning will help in diagnosis and the prediction of disease spread. The editors present a comprehensive review of research applying deep learning in health informatics in the fields of medical imaging, electronic health records, genomics, and sensing, and highlights various challenges in applying deep learning in health care. This

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

Handbook of Deep Learning in Biomedical Engineering and Health Informatics
  • Author : E. Golden Julie,Y. Harold Robinson,S. M. Jaisakthi
  • Publisher : CRC Press
  • Release : 22 September 2021
GET THIS BOOK Handbook of Deep Learning in Biomedical Engineering and Health Informatics

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis

Deep Learning Machine Learning and Iot in Biomedical and Health Informatics

Deep Learning  Machine Learning and Iot in Biomedical and Health Informatics
  • Author : Sujata Dash,Subhendu Kumar Pani,Joel Jose Coelho Rodrigues,Babita Majhi
  • Publisher : CRC Press
  • Release : 12 January 2022
GET THIS BOOK Deep Learning Machine Learning and Iot in Biomedical and Health Informatics

Biomedical and Health Informatics is an important field that brings tremendous opportunities and helps address challenges due to an abundance of available biomedical data. This book examines and demonstrates state-of-the-art approaches for IOT and Machine Learning based biomedical and health related applications. This book aims to provide computational methods for accumulating, updating and changing knowledge in intelligent systems and particularly learning mechanisms that help us to induce knowledge from the data. It is helpful in cases where direct algorithmic solutions

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
  • Author : Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
  • Publisher : Academic Press
  • Release : 14 January 2020
GET THIS BOOK Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they

Machine Learning for Health Informatics

Machine Learning for Health Informatics
  • Author : Andreas Holzinger
  • Publisher : Springer
  • Release : 09 December 2016
GET THIS BOOK Machine Learning for Health Informatics

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds,

Biomedical Data Mining for Information Retrieval

Biomedical Data Mining for Information Retrieval
  • Author : Subhendu Kumar Pani,Sujata Dash,S. Balamurugan,Ajith Abraham
  • Publisher : John Wiley & Sons
  • Release : 06 August 2021
GET THIS BOOK Biomedical Data Mining for Information Retrieval

This book comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and Health Informatics is an emerging field of research at the intersection of information science, computer science, and health care and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including

Smart Computational Intelligence in Biomedical and Health Informatics

Smart Computational Intelligence in Biomedical and Health Informatics
  • Author : Amit Kumar Manocha,Mandeep Singh,Shruti Jain,Vishal Jain
  • Publisher : CRC Press
  • Release : 27 September 2021
GET THIS BOOK Smart Computational Intelligence in Biomedical and Health Informatics

Smart Computational Intelligence in Biomedical and Health Informatics presents state-of-the-art innovations; research, design, and implementation of methodological and algorithmic solutions to data processing problems, including analysis of evolving trends in health informatics and computer-aided diagnosis. This book describes practical, applications-led research regarding the use of methods and devices in clinical diagnosis, disease prevention, and patient monitoring and management. It also covers simulation and modeling, measurement and control, analysis, information extraction and monitoring of physiological data in clinical medicine and the

Predictive Intelligence in Biomedical and Health Informatics

Predictive Intelligence in Biomedical and Health Informatics
  • Author : Rajshree Srivastava,Nhu Gia Nguyen,Ashish Khanna,Siddhartha Bhattacharyya
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 12 October 2020
GET THIS BOOK Predictive Intelligence in Biomedical and Health Informatics

Predictive Intelligence in Biomedical and Health Informatics focuses on imaging, computer-aided diagnosis and therapy as well as intelligent biomedical image processing and analysis. It develops computational models, methods and tools for biomedical engineering related to computer-aided diagnostics (CAD), computer-aided surgery (CAS), computational anatomy and bioinformatics. Large volumes of complex data are often a key feature of biomedical and engineering problems and computational intelligence helps to address such problems. Practical and validated solutions to hard biomedical and engineering problems can be

Signal Processing Techniques for Computational Health Informatics

Signal Processing Techniques for Computational Health Informatics
  • Author : Md Atiqur Rahman Ahad,Mosabber Uddin Ahmed
  • Publisher : Springer Nature
  • Release : 07 October 2020
GET THIS BOOK Signal Processing Techniques for Computational Health Informatics

This book focuses on signal processing techniques used in computational health informatics. As computational health informatics is the interdisciplinary study of the design, development, adoption and application of information and technology-based innovations, specifically, computational techniques that are relevant in health care, the book covers a comprehensive and representative range of signal processing techniques used in biomedical applications, including: bio-signal origin and dynamics, sensors used for data acquisition, artefact and noise removal techniques, feature extraction techniques in the time, frequency, time–

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
  • Author : Om Prakash Jena,Bharat Bhushan,Nitin Rakesh,Parma Nand Astya,Yousef Farhaoui
  • Publisher : CRC Press
  • Release : 01 December 2021
GET THIS BOOK Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems

The paramountcy of medical informatics is to improve life expectancy, disease diagnosis and quality of life. Medical devices have revolutionized healthcare and led to the modern age of machine learning, deep learning and internet of medical things (IoMT) with their proliferation, mobility and agility. This book will expose different dimensions of applications for computational intelligence and will explain its use in solving various biomedical and healthcare problems in the real world. This book describes the fundamental concepts of machine learning

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

Handbook of Deep Learning in Biomedical Engineering and Health Informatics
  • Author : E. Golden Julie,Y. Harold Robinson,S. M. Jaisakthi
  • Publisher : CRC Press
  • Release : 22 September 2021
GET THIS BOOK Handbook of Deep Learning in Biomedical Engineering and Health Informatics

This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis

Deep Learning and Parallel Computing Environment for Bioengineering Systems

Deep Learning and Parallel Computing Environment for Bioengineering Systems
  • Author : Arun Kumar Sangaiah
  • Publisher : Academic Press
  • Release : 26 July 2019
GET THIS BOOK Deep Learning and Parallel Computing Environment for Bioengineering Systems

Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major

Computational Intelligence for Machine Learning and Healthcare Informatics

Computational Intelligence for Machine Learning and Healthcare Informatics
  • Author : Rajshree Srivastava,Pradeep Kumar Mallick,Siddharth Swarup Rautaray,Manjusha Pandey
  • Publisher : Walter de Gruyter GmbH & Co KG
  • Release : 22 June 2020
GET THIS BOOK Computational Intelligence for Machine Learning and Healthcare Informatics

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.