Deep Learning for Biomedical Applications

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  • Publisher : CRC Press
  • Release : 20 July 2021
  • ISBN : 9781000406429
  • Page : 364 pages
  • Rating : 4.5/5 from 103 voters

Download Deep Learning for Biomedical Applications in PDF, Epub and Kindle

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.

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Deep Learning for Biomedical Applications

Deep Learning for Biomedical Applications
  • Author : Utku Kose,Omer Deperlioglu,D. Jude Hemanth
  • Publisher : CRC Press
  • Release Date : 2021-07-20
  • ISBN : 9781000406429
GET THIS BOOKDeep Learning for Biomedical Applications

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series,

Handbook of Deep Learning in Biomedical Engineering

Handbook of Deep Learning in Biomedical Engineering
  • Author : Valentina Emilia Balas,Brojo Kishore Mishra,Raghvendra Kumar
  • Publisher : Academic Press
  • Release Date : 2020-11-12
  • ISBN : 9780128230473
GET THIS BOOKHandbook of Deep Learning in Biomedical Engineering

Deep Learning (DL) is a method of machine learning, running over Artificial Neural Networks, that uses multiple layers to extract high-level features from large amounts of raw data. Deep Learning methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of Deep Learning and its applications in the field of Biomedical Engineering. Deep learning has been

Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications
  • Author : Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch
  • Publisher : Academic Press
  • Release Date : 2019-11-29
  • ISBN : 9780128144831
GET THIS BOOKComputational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes

Machine Learning for Healthcare Applications

Machine Learning for Healthcare Applications
  • Author : Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar
  • Publisher : John Wiley & Sons
  • Release Date : 2021-04-13
  • ISBN : 9781119791812
GET THIS BOOKMachine Learning for Healthcare Applications

When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Deep Neural Networks for Multimodal Imaging and Biomedical Applications
  • Author : Suresh, Annamalai,Udendhran, R.,Vimal, S.
  • Publisher : IGI Global
  • Release Date : 2020-06-26
  • ISBN : 9781799835929
GET THIS BOOKDeep Neural Networks for Multimodal Imaging and Biomedical Applications

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the

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 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

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

Machine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine
  • Author : Subhi J. Al'Aref,Gurpreet Singh,Lohendran Baskaran,Dimitri Metaxas
  • Publisher : Academic Press
  • Release Date : 2020-11-20
  • ISBN : 9780128202746
GET THIS BOOKMachine Learning in Cardiovascular Medicine

Machine Learning in Cardiovascular Medicine addresses the ever-expanding applications of artificial intelligence (AI), specifically machine learning (ML), in healthcare and within cardiovascular medicine. The book focuses on emphasizing ML for biomedical applications and provides a comprehensive summary of the past and present of AI, basics of ML, and clinical applications of ML within cardiovascular medicine for predictive analytics and precision medicine. It helps readers understand how ML works along with its limitations and strengths, such that they can could harness

Handbook of Artificial Intelligence in Biomedical Engineering

Handbook of Artificial Intelligence in Biomedical Engineering
  • Author : Krishnan Saravanan,Ramesh Kesavan,B. Surendiran,G. S. Mahalakshmi
  • Publisher : Unknown
  • Release Date : 2021
  • ISBN : 1003045561
GET THIS BOOKHandbook of Artificial Intelligence in Biomedical Engineering

"Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques, such as machine learning, Internet of Things (IoT), and big data, accelerate the deployment of biomedical devices in various healthcare applications. This volume explores how artificial intelligence (AI) can be applied to these expert systems by mimicking the human expert's knowledge in order to predict and monitor the

Deep Learning for Biomedical Data Analysis

Deep Learning for Biomedical Data Analysis
  • Author : Mourad Elloumi
  • Publisher : Springer
  • Release Date : 2022-07-15
  • ISBN : 3030716783
GET THIS BOOKDeep Learning for Biomedical Data Analysis

This book is the first overview on Deep Learning (DL) for biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
  • Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
  • Publisher : Academic Press
  • Release Date : 2021-04-26
  • ISBN : 9780128232170
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and

Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning

Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning
  • Author : Richard Segall,Gao Niu
  • Publisher : Engineering Science Reference
  • Release Date : 2021-11
  • ISBN : 1799884554
GET THIS BOOKBiomedical and Business Applications Using Artificial Neural Networks and Machine Learning

"This book covers applications of artificial neural networks (ANN) and machine learning (ML) aspects of artificial intelligence to applications to the biomedical and business world including their interface to applications for screening for diseases to applications to large-scale credit card purchasing patterns"--

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models
  • Author : Jorge Garza Ulloa
  • Publisher : Elsevier
  • Release Date : 2021-12-06
  • ISBN : 9780128209349
GET THIS BOOKApplied Biomedical Engineering Using Artificial Intelligence and Cognitive Models

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data
  • Author : Ervin Sejdic,Tiago H. Falk
  • Publisher : CRC Press
  • Release Date : 2018-07-04
  • ISBN : 9781351061216
GET THIS BOOKSignal Processing and Machine Learning for Biomedical Big Data

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will describe signal processing, machine learning, and parallel computing strategies to revolutionize the world of medical analytics and diagnosis as presented by world class researchers and experts in this important field. The chapters will desribe tools that can be used by biomedical and clinical practitioners as well as industry professionals. It will give