Deep Learning Techniques for Biomedical and Health Informatics

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  • Publisher : Academic Press
  • Release : 14 January 2020
  • ISBN : 9780128190623
  • Page : 367 pages
  • Rating : 4.5/5 from 103 voters

Download Deep Learning Techniques for Biomedical and Health Informatics in PDF, Epub and Kindle

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 are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

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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 Date : 2020-01-14
  • ISBN : 9780128190623
GET THIS BOOKDeep 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

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 Date : 2021-08-06
  • ISBN : 9781119711261
GET THIS BOOKBiomedical 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

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 J. P. C. Rodrigues,Babita Majhi
  • Publisher : CRC Press
  • Release Date : 2022-02-11
  • ISBN : 9781000534054
GET THIS BOOKDeep 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 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 Date : 2021-09-26
  • ISBN : 9781000429084
GET THIS BOOKDeep 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 Date : 2021-09-22
  • ISBN : 9781000370492
GET THIS BOOKHandbook 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 in Bioinformatics

Deep Learning in Bioinformatics
  • Author : Habib Izadkhah
  • Publisher : Academic Press
  • Release Date : 2022-01-17
  • ISBN : 9780128238363
GET THIS BOOKDeep Learning in Bioinformatics

Deep Learning in Bioinformatics: Techniques and Applications in Practice introduces the topic in an easy-to-understand way, exploring how it can be utilized for addressing important problems in bioinformatics, including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction, and in systems biology. The book also presents theoretical and practical successes of deep learning in bioinformatics, pointing out problems and suggesting future research directions. Dr. Izadkhah

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 Date : 2021-09-27
  • ISBN : 9781000429121
GET THIS BOOKDeep 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

Machine Learning for Health Informatics

Machine Learning for Health Informatics
  • Author : Andreas Holzinger
  • Publisher : Springer
  • Release Date : 2016-12-09
  • ISBN : 9783319504780
GET THIS BOOKMachine 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,

Computational Intelligence and Healthcare Informatics

Computational Intelligence and Healthcare Informatics
  • Author : Om Prakash Jena,Alok Ranjan Tripathy,Ahmed A. Elngar,Zdzislaw Polkowski
  • Publisher : John Wiley & Sons
  • Release Date : 2021-10-19
  • ISBN : 9781119818687
GET THIS BOOKComputational Intelligence and Healthcare Informatics

AI techniques are being successfully used in the fields of health to increase the efficacy of therapies and avoid the risks of false diagnosis, therapeutic decision-making, and outcome prediction in many clinical cases, thanks to the rapid advancement of technology. The acquisition, analysis, and application of a vast amount of information required to solve complex problems is a challenge for modern health therapies. The 21 chapters in this integrate several aspects of computational intelligence like machine learning and deep learning from

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications
  • Author : K. G. Srinivasa,G. M. Siddesh,S. R. Manisekhar
  • Publisher : Springer Nature
  • Release Date : 2020-01-30
  • ISBN : 9789811524455
GET THIS BOOKStatistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

Machine Learning for Non/Less-Invasive Methods in Health Informatics

Machine Learning for Non/Less-Invasive Methods in Health Informatics
  • Author : Kun Qian,Liang Zhang,Kezhi Li,Juan Liu
  • Publisher : Frontiers Media SA
  • Release Date : 2021-11-26
  • ISBN : 9782889717088
GET THIS BOOKMachine Learning for Non/Less-Invasive Methods in Health Informatics

Introduction to Machine Learning and Bioinformatics

Introduction to Machine Learning and Bioinformatics
  • Author : Sushmita Mitra,Sujay Datta,Theodore Perkins,George Michailidis
  • Publisher : CRC Press
  • Release Date : 2008-06-05
  • ISBN : 9781420011784
GET THIS BOOKIntroduction to Machine Learning and Bioinformatics

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas relate to each other. Examines Connections between Machine Learning & Bioinformatics The book begins with a brief historical overview of the technological developments in biology. It then describes the main problems in bioinformatics and the fundamental concepts and algorithms of machine learning. After forming this foundation, the authors

Data Analytics in Bioinformatics

Data Analytics in Bioinformatics
  • Author : Rabinarayan Satpathy,Tanupriya Choudhury,Suneeta Satpathy,Sachi Nandan Mohanty,Xiaobo Zhang
  • Publisher : John Wiley & Sons
  • Release Date : 2021-01-20
  • ISBN : 9781119785606
GET THIS BOOKData Analytics in Bioinformatics

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of

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 Date : 2019-07-26
  • ISBN : 9780128172933
GET THIS BOOKDeep 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

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 Date : 2020-10-07
  • ISBN : 9783030549329
GET THIS BOOKSignal 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–