Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128176733
Total Pages : 456 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by : Abdulhamit Subasi

Download or read book Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and published by Academic Press. This book was released on 2019-03-16 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction Explains how to apply machine learning techniques to EEG, ECG and EMG signals Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Practical Machine Learning for Data Analysis Using Python

Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128213809
Total Pages : 534 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Practical Machine Learning for Data Analysis Using Python by : Abdulhamit Subasi

Download or read book Practical Machine Learning for Data Analysis Using Python written by Abdulhamit Subasi and published by Academic Press. This book was released on 2020-06-05 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features

Practical Biomedical Signal Analysis Using MATLAB®

Author : Katarzyna J. Blinowska
Publisher : CRC Press
ISBN 13 : 0429775733
Total Pages : 370 pages
Book Rating : 4.4/5 (297 download)

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Book Synopsis Practical Biomedical Signal Analysis Using MATLAB® by : Katarzyna J. Blinowska

Download or read book Practical Biomedical Signal Analysis Using MATLAB® written by Katarzyna J. Blinowska and published by CRC Press. This book was released on 2021-10-18 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the latest cutting-edge techniques in biomedical signal processing while presenting a coherent treatment of various signal processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB® also offers practical guidance on which procedures are appropriate for a given task and different types of data. It begins by describing signal analysis techniques—including the newest and most advanced methods in the field—in an easy and accessible way, illustrating them with Live Script demos. MATLAB® routines are listed when available, and freely available software is discussed where appropriate. The book concludes by exploring the applications of the methods to a broad range of biomedical signals while highlighting common problems encountered in practice. These chapters have been updated throughout and include new sections on multiple channel analysis and connectivity measures, phase-amplitude analysis, functional near-infrared spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis, and brain-computer interfaces. By providing a unified overview of the field, this book explains how to integrate signal processing techniques in biomedical applications properly and explores how to avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. It will be an excellent guide for graduate students studying biomedical engineering and practicing researchers in the field of biomedical signal analysis. Features: Fully updated throughout with new achievements, technologies, and methods and is supported with over 40 original MATLAB Live Scripts illustrating the discussed techniques, suitable for self-learning or as a supplement to college courses Provides a practical comparison of the advantages and disadvantages of different approaches in the context of various applications Applies the methods to a variety of signals, including electric, magnetic, acoustic, and optical Katarzyna J. Blinowska is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications. Jarosław Żygierewicz is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, and applications of machine learning in signal processing and classification.

Practical Biomedical Signal Analysis Using MATLAB

Author : Katarzyna J. Blinowska-Cieślak
Publisher :
ISBN 13 : 9781032105529
Total Pages : pages
Book Rating : 4.1/5 (55 download)

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Book Synopsis Practical Biomedical Signal Analysis Using MATLAB by : Katarzyna J. Blinowska-Cieślak

Download or read book Practical Biomedical Signal Analysis Using MATLAB written by Katarzyna J. Blinowska-Cieślak and published by . This book was released on 2021-09 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Fully updated and with exclusive new content, this second edition presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data"--

Practical Biomedical Signal Analysis Using MATLAB®

Author : Katarzyn J. Blinowska
Publisher : CRC Press
ISBN 13 : 1439812020
Total Pages : 326 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Practical Biomedical Signal Analysis Using MATLAB® by : Katarzyn J. Blinowska

Download or read book Practical Biomedical Signal Analysis Using MATLAB® written by Katarzyn J. Blinowska and published by CRC Press. This book was released on 2011-09-12 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice. A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods.

Signal Processing and Machine Learning for Biomedical Big Data

Author : Ervin Sejdic
Publisher : CRC Press
ISBN 13 : 149877346X
Total Pages : 624 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Signal Processing and Machine Learning for Biomedical Big Data by : Ervin Sejdic

Download or read book Signal Processing and Machine Learning for Biomedical Big Data written by Ervin Sejdic and published by CRC Press. This book was released on 2018-07-04 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 thus discusses modalities; the numerous ways in which this data is captured via sensors; and various sample rates and dimensionalities. Capturing, analyzing, storing, and visualizing such massive data has required new shifts in signal processing paradigms and new ways of combining signal processing with machine learning tools. This book covers several of these aspects in two ways: firstly, through theoretical signal processing chapters where tools aimed at big data (be it biomedical or otherwise) are described; and, secondly, through application-driven chapters focusing on existing applications of signal processing and machine learning for big biomedical data. This text aimed at the curious researcher working in the field, as well as undergraduate and graduate students eager to learn how signal processing can help with big data analysis. It is the hope of Drs. Sejdic and Falk that this book will bring together signal processing and machine learning researchers to unlock existing bottlenecks within the healthcare field, thereby improving patient quality-of-life. Provides an overview of recent state-of-the-art signal processing and machine learning algorithms for biomedical big data, including applications in the neuroimaging, cardiac, retinal, genomic, sleep, patient outcome prediction, critical care, and rehabilitation domains. Provides contributed chapters from world leaders in the fields of big data and signal processing, covering topics such as data quality, data compression, statistical and graph signal processing techniques, and deep learning and their applications within the biomedical sphere. This book’s material covers how expert domain knowledge can be used to advance signal processing and machine learning for biomedical big data applications.

Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning

Author : Saeed Mian Qaisar
Publisher : Springer Nature
ISBN 13 : 3031232399
Total Pages : 385 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning by : Saeed Mian Qaisar

Download or read book Advances in Non-Invasive Biomedical Signal Sensing and Processing with Machine Learning written by Saeed Mian Qaisar and published by Springer Nature. This book was released on 2023-03-01 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the modern technological advancements and revolutions in the biomedical sector. Progress in the contemporary sensing, Internet of Things (IoT) and machine learning algorithms and architectures have introduced new approaches in the mobile healthcare. A continuous observation of patients with critical health situation is required. It allows monitoring of their health status during daily life activities such as during sports, walking and sleeping. It is realizable by intelligently hybridizing the modern IoT framework, wireless biomedical implants and cloud computing. Such solutions are currently under development and in testing phases by healthcare and governmental institutions, research laboratories and biomedical companies. The biomedical signals such as electrocardiogram (ECG), electroencephalogram (EEG), Electromyography (EMG), phonocardiogram (PCG), Chronic Obstructive Pulmonary (COP), Electrooculography (EoG), photoplethysmography (PPG), and image modalities such as positron emission tomography (PET), magnetic resonance imaging (MRI) and computerized tomography (CT) are non-invasively acquired, measured, and processed via the biomedical sensors and gadgets. These signals and images represent the activities and conditions of human cardiovascular, neural, vision and cerebral systems. Multi-channel sensing of these signals and images with an appropriate granularity is required for an effective monitoring and diagnosis. It renders a big volume of data and its analysis is not feasible manually. Therefore, automated healthcare systems are in the process of evolution. These systems are mainly based on biomedical signal and image acquisition and sensing, preconditioning, features extraction and classification stages. The contemporary biomedical signal sensing, preconditioning, features extraction and intelligent machine and deep learning-based classification algorithms are described. Each chapter starts with the importance, problem statement and motivation. A self-sufficient description is provided. Therefore, each chapter can be read independently. To the best of the editors’ knowledge, this book is a comprehensive compilation on advances in non-invasive biomedical signal sensing and processing with machine and deep learning. We believe that theories, algorithms, realizations, applications, approaches, and challenges, which are presented in this book will have their impact and contribution in the design and development of modern and effective healthcare systems.

Biomedical Signal Processing

Author : Ganesh R. Naik
Publisher : CRC Press
ISBN 13 : 1000906485
Total Pages : 313 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis Biomedical Signal Processing by : Ganesh R. Naik

Download or read book Biomedical Signal Processing written by Ganesh R. Naik and published by CRC Press. This book was released on 2023-09-27 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications. Features: Explains signal processing of neuroscience applications using modern data science techniques. Provides comprehensible review on biomedical signals nature and acquisition aspects. Focusses on selected applications of neurosciences, cardiovascular and muscle-related biomedical areas. Includes computational intelligence, machine learning and biomedical signal processing and analysis. Reviews theoretical basis of deep learning and state-of-the-art biomedical signal processing and analysis. This book is aimed at researchers, graduate students in biomedical signal processing, signal processing, electrical engineering, neuroscience and computer science.

Biomedical Signal Analysis

Author : Rangaraj M. Rangayyan
Publisher : John Wiley & Sons
ISBN 13 : 1119067936
Total Pages : 720 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Biomedical Signal Analysis by : Rangaraj M. Rangayyan

Download or read book Biomedical Signal Analysis written by Rangaraj M. Rangayyan and published by John Wiley & Sons. This book was released on 2015-04-24 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications 800 mathematical expressions and equations Practical questions, problems and laboratory exercises Includes fractals and chaos theory with biomedical applications

Machine Intelligence and Signal Analysis

Author : M. Tanveer
Publisher : Springer
ISBN 13 : 981130923X
Total Pages : 767 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Machine Intelligence and Signal Analysis by : M. Tanveer

Download or read book Machine Intelligence and Signal Analysis written by M. Tanveer and published by Springer. This book was released on 2018-08-07 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Advanced Methods in Biomedical Signal Processing and Analysis

Author : Kunal Pal
Publisher : Academic Press
ISBN 13 : 0323859542
Total Pages : 434 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Advanced Methods in Biomedical Signal Processing and Analysis by : Kunal Pal

Download or read book Advanced Methods in Biomedical Signal Processing and Analysis written by Kunal Pal and published by Academic Press. This book was released on 2022-09-07 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 signal processing Includes machine and deep learning methods Presents experimental case studies

Signal Processing for Neuroscientists

Author : Wim van Drongelen
Publisher : Elsevier
ISBN 13 : 9780080467757
Total Pages : 320 pages
Book Rating : 4.4/5 (677 download)

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Book Synopsis Signal Processing for Neuroscientists by : Wim van Drongelen

Download or read book Signal Processing for Neuroscientists written by Wim van Drongelen and published by Elsevier. This book was released on 2006-12-18 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Biomedical Signal Processing for Healthcare Applications

Author : Varun Bajaj
Publisher : CRC Press
ISBN 13 : 1000413306
Total Pages : 336 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Biomedical Signal Processing for Healthcare Applications by : Varun Bajaj

Download or read book Biomedical Signal Processing for Healthcare Applications written by Varun Bajaj and published by CRC Press. This book was released on 2021-07-21 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Photoplethysmography

Author : Panicos A. Kyriacou
Publisher : Academic Press
ISBN 13 : 012823525X
Total Pages : 508 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Photoplethysmography by : Panicos A. Kyriacou

Download or read book Photoplethysmography written by Panicos A. Kyriacou and published by Academic Press. This book was released on 2021-11-03 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in wearable sensors and PPG for cardiovascular assessment. Presents the underlying principles and technology surrounding PPG Includes applications for healthcare and wellbeing Focuses on PPG in wearable sensors and devices Presents advanced signal analysis techniques Includes cutting-edge research, applications and future directions

Sub-Terahertz Sensing Technology for Biomedical Applications

Author : Shiban Kishen Koul
Publisher : Springer Nature
ISBN 13 : 9811931402
Total Pages : 289 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Sub-Terahertz Sensing Technology for Biomedical Applications by : Shiban Kishen Koul

Download or read book Sub-Terahertz Sensing Technology for Biomedical Applications written by Shiban Kishen Koul and published by Springer Nature. This book was released on 2022-08-20 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers the readers an opportunity to acquire the concepts of artificial intelligence (AI) enabled sub-THz systems for novel applications in the biomedical field. The readers will also be inspired to contextualize these applications for solving real life problems such as non-invasive glucose monitoring systems, cancer detection and dental imaging. The introductory section of this book focuses on existing technologies for radio frequency and infrared sensing in biomedical applications, and their limited use in sensing applications, as well as the advantages of using THz technology in this context. This is followed by a detailed comparative analysis of THz electronics technology and other conventional electro optic THz setups highlighting the superior efficiency, affordability and portability of electronics-based THz systems. The book also discusses electronic sub-THz measurement systems for different biomedical applications. The chapters elucidate two major applications where sub-THz provides an edge over existing state of the art techniques used for non-invasive measurement of blood glucose levels and intraoperative assessment of tumor margins. There is a detailed articulation of an application of leveraging machine learning for measurement systems for non-invasive glucose concentration measurement. This helps the reader relate to the output in a more user-friendly format and understand the possible use cases in a more lucid manner. The book is intended to help the reader learn how to build tissue phantoms and characterize them at sub-THz frequencies in order to test the measurement systems. Towards the end of the book, a brief introduction to system automation for biomedical imaging is provided as well for quick analysis of the data. The book will empower the reader to understand and appreciate the immense possibilities of using electronic THz systems in the biomedical field, creating gateways for fueling further research in this area.

Enhanced Telemedicine and e-Health

Author : Gonçalo Marques
Publisher : Springer Nature
ISBN 13 : 3030701115
Total Pages : 359 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Enhanced Telemedicine and e-Health by : Gonçalo Marques

Download or read book Enhanced Telemedicine and e-Health written by Gonçalo Marques and published by Springer Nature. This book was released on 2021-05-09 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, new applications on computer-aided technologies for telemedicine have emerged. Therefore, it is essential to capture this growing research area concerning the requirements of telemedicine. This book presents the latest findings on soft computing, artificial intelligence, Internet of Things and related computer-aided technologies for enhanced telemedicine and e-health. Furthermore, this volume includes comprehensive reviews describing procedures and techniques, which are crucial to support researchers in the field who want to replicate these methodologies in solving their related research problems. On the other hand, the included case studies present novel approaches using computer-aided methods for enhanced telemedicine and e-health. This volume aims to support future research activities in this domain. Consequently, the content has been selected to support not only academics or engineers but also to be used by healthcare professionals.

Applications of Artificial Intelligence in Healthcare and Biomedicine

Author : Abdulhamit Subasi
Publisher : Elsevier
ISBN 13 : 0443223092
Total Pages : 550 pages
Book Rating : 4.4/5 (432 download)

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Book Synopsis Applications of Artificial Intelligence in Healthcare and Biomedicine by : Abdulhamit Subasi

Download or read book Applications of Artificial Intelligence in Healthcare and Biomedicine written by Abdulhamit Subasi and published by Elsevier. This book was released on 2024-03-22 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: ??Applications of Artificial Intelligence in Healthcare and Biomedicine provides ?updated knowledge on the applications of artificial intelligence in medical image analysis. The book starts with an introduction to Artificial Intelligence techniques for Healthcare and Biomedicine. In 16 chapters it presents artificial applications in Electrocardiogram (ECG), Electroencephalogram (EEG) and Electromyography (EMG), signal analysis, Computed Tomography (CT), Magnetic Resonance Imaging (MR) and Ultrasound image analysis. It equips researchers with tools for early breast cancer detection from mammograms using artificial intelligence (AI), AI models to detect lung cancer using histopathological images and a deep learning-based approach to get a proper and faster diagnosis of the Optical Coherence Tomography (OCT) images. It also presents present 3D medical image analysis using 3D Convolutional Neural Networks (CNNs). Applications of Artificial Intelligence in Healthcare and Biomedicine closes with a chapter on AI-based approach to forecast diabetes patients' hospital re-admissions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about the applications of Artificial Intelligence and its impact in medical/biomedical image analysis. Provides knowledge on Artificial Intelligence algorithms for clinical data analysis Gives insights into both AI applications in biomedical signal analysis, biomedical image analysis, and applications in healthcare, including drug discovery Equips researchers with tools for early breast cancer detection