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Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
  • Author : Walid A. Zgallai
  • Publsiher : Academic Press
  • Release : 19 August 2020
  • ISBN : 0128189460
  • Pages : 268 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Summary:
Biomedical Signal Processing with Artificial Intelligence, a new volume in the Developments in Biomedical Engineering and Bioelectronics series, covers the basics of analog and digital data and data acquisition. The book explains the role of smart sensors, smart materials and wearables in relation to biomedical signals. It also provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Machine Learning, including Deep Learning, Neural Networks, and the implications of the expansion of artificial intelligence is also covered, as are biomedical images and their segmentation, classification and detection. This book covers all aspects of signals, from acquisition, the use of hardware and software, analyzing signals, and making use of AI in problem-solving. Developments in Biomedical Engineering and Bioelectronics is a 10-volume series which covers recent developments, trends and advances in this field. Edited by leading academics in the field, and taking a multidisciplinary approach, this series is a forum for cutting-edge, contemporary review articles and contributions from key 'up-and-coming' academics across the full subject area. Presents comprehensive coverage and the latest advances and applications in biomedical signal processing Contains contributions from recognized researchers and field leaders Includes online presentations, tutorials, applications and algorithm examples


Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
  • Author : Walid A. Zgallai
  • Publisher : Academic Press
  • Release : 19 August 2020
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing with Artificial Intelligence, a new volume in the Developments in Biomedical Engineering and Bioelectronics series, covers the basics of analog and digital data and data acquisition. The book explains the role of smart sensors, smart materials and wearables in relation to biomedical signals. It also provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of Machine Learning, including Deep Learning, Neural Networks,

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Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
  • Author : Walid A. Zgallai
  • Publisher : Academic Press
  • Release : 29 July 2020
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of

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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 : 19 August 2022
GET THIS BOOKSignal Processing and Machine Learning for Biomedical Big Data

Within the healthcare domain, big data is defined as any ``high volume, high diversity biological, clinical, environmental, and lifestyle information collected from single individuals to large cohorts, in relation to their health and wellness status, at one or several time points.'' Such data is crucial because within it lies vast amounts of invaluable information that could potentially change a patient's life, opening doors to alternate therapies, drugs, and diagnostic tools. Signal Processing and Machine Learning for Biomedical Big Data

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
  • Author : Nilanjan Dey,Surekha Borra,Amira Ashour,Fuqian Shi
  • Publisher : Academic Press
  • Release : 15 January 2019
GET THIS BOOKMachine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as

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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 : 26 April 2021
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

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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 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–

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Advanced Methods in Biomedical Signal Processing and Analysis

Advanced Methods in Biomedical Signal Processing and Analysis
  • Author : Kunal Pal,Samit Ari,Arindam Bit,Saugat Bhattacharyya
  • Publisher : Academic Press
  • Release : 15 June 2022
GET THIS BOOKAdvanced Methods in Biomedical Signal Processing and Analysis

Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. Gives advanced methods in

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
  • Author : Abdulhamit Subasi
  • Publisher : Academic Press
  • Release : 16 March 2019
GET THIS BOOKPractical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques,

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Biomedical Signal Processing for Healthcare Applications

Biomedical Signal Processing for Healthcare Applications
  • Author : Varun Bajaj,G. R. Sinha,Chinmay Chakraborty
  • Publisher : CRC Press
  • Release : 21 July 2021
GET THIS BOOKBiomedical Signal Processing for Healthcare Applications

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal

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Applications of Artificial Intelligence in Medical Imaging

Applications of Artificial Intelligence in Medical Imaging
  • Author : Abdulhamit Subasi
  • Publisher : Academic Press
  • Release : 15 November 2022
GET THIS BOOKApplications of Artificial Intelligence in Medical Imaging

Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's,

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Biomedical Signal and Image Processing in Patient Care

Biomedical Signal and Image Processing in Patient Care
  • Author : Kolekar, Maheshkumar H.,Kumar, Vinod
  • Publisher : IGI Global
  • Release : 11 August 2017
GET THIS BOOKBiomedical Signal and Image Processing in Patient Care

In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally

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AI-Enabled Smart Healthcare Using Biomedical Signals

AI-Enabled Smart Healthcare Using Biomedical Signals
  • Author : Chaurasiya, Rahul Kumar,Agrawal, Dheeraj,Pachori, Ram Bilas
  • Publisher : IGI Global
  • Release : 27 May 2022
GET THIS BOOKAI-Enabled Smart Healthcare Using Biomedical Signals

Technological advancements have enhanced all functions of society and revolutionized the healthcare field. Smart healthcare applications and practices have grown within the past decade, strengthening overall care. Biomedical signals observe physiological activities, which provide essential information to healthcare professionals. Biomedical signal processing can be optimized through artificial intelligence (AI) and machine learning (ML), presenting the next step towards smart healthcare. AI-Enabled Smart Healthcare Using Biomedical Signals will not only cover the mathematical description of the AI- and ML-based methods, but

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Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Adam Bohr,Kaveh Memarzadeh
  • Publisher : Academic Press
  • Release : 21 June 2020
GET THIS BOOKArtificial Intelligence in Healthcare

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its

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Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems
  • Author : E. Priya,V. Rajinikanth
  • Publisher : Springer Nature
  • Release : 21 September 2020
GET THIS BOOKSignal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a

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Big Data Analytics and Artificial Intelligence in the Healthcare Industry

Big Data Analytics and Artificial Intelligence in the Healthcare Industry
  • Author : Machado, José,Peixoto, Hugo,Sousa, Regina
  • Publisher : IGI Global
  • Release : 29 April 2022
GET THIS BOOKBig Data Analytics and Artificial Intelligence in the Healthcare Industry

Developing new approaches and reliable enabling technologies in the healthcare industry is needed to enhance our overall quality of life and lead to a healthier, innovative, and secure society. Further study is required to ensure these current technologies, such as big data analytics and artificial intelligence, are utilized to their utmost potential and are appropriately applied to advance society. Big Data Analytics and Artificial Intelligence in the Healthcare Industry discusses technologies and emerging topics regarding reliable and innovative solutions applied

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