Machine Learning In Bio Signal Analysis And Diagnostic Imaging

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Machine Learning in Bio Signal Analysis and Diagnostic Imaging Book PDF

Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Publisher : Academic Press
Page : 345 pages
File Size : 41,5 Mb
Release : 2018-11-30
Category : Science
ISBN : 9780128160879

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi Pdf

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 PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods

Kemal Polat,Saban Öztürk
Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods Book PDF

Author : Kemal Polat,Saban Öztürk
Publisher : Elsevier
Page : 303 pages
File Size : 44,7 Mb
Release : 2023-04-30
Category : Computers
ISBN : 9780323996815

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Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods by Kemal Polat,Saban Öztürk Pdf

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important Includes novel methodologies, datasets, design and simulation examples

Signal Processing in Medicine and Biology

Iyad Obeid,Ivan Selesnick,Joseph Picone
Signal Processing in Medicine and Biology Book PDF

Author : Iyad Obeid,Ivan Selesnick,Joseph Picone
Publisher : Springer Nature
Page : 287 pages
File Size : 43,7 Mb
Release : 2020-03-16
Category : Technology & Engineering
ISBN : 9783030368449

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Signal Processing in Medicine and Biology by Iyad Obeid,Ivan Selesnick,Joseph Picone Pdf

This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson’s; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Abdulhamit Subasi
Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Book PDF

Author : Abdulhamit Subasi
Publisher : Academic Press
Page : 456 pages
File Size : 46,9 Mb
Release : 2019-03-16
Category : Business & Economics
ISBN : 9780128176733

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by Abdulhamit Subasi Pdf

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

Machine Learning and AI Techniques in Interactive Medical Image Analysis

Panigrahi, Lipismita,Biswal, Sandeep,Bhoi, Akash Kumar,Kalam, Akhtar,Barsocchi, Paolo
Machine Learning and AI Techniques in Interactive Medical Image Analysis Book PDF

Author : Panigrahi, Lipismita,Biswal, Sandeep,Bhoi, Akash Kumar,Kalam, Akhtar,Barsocchi, Paolo
Publisher : IGI Global
Page : 241 pages
File Size : 50,5 Mb
Release : 2022-09-16
Category : Medical
ISBN : 9781668446737

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Machine Learning and AI Techniques in Interactive Medical Image Analysis by Panigrahi, Lipismita,Biswal, Sandeep,Bhoi, Akash Kumar,Kalam, Akhtar,Barsocchi, Paolo Pdf

The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians.

Deep Learning in Biomedical Signal and Medical Imaging

Ngangbam Herojit Singh,Utku Kose,Sarada Prasad Gochhayat
Deep Learning in Biomedical Signal and Medical Imaging Book PDF

Author : Ngangbam Herojit Singh,Utku Kose,Sarada Prasad Gochhayat
Publisher : Unknown
Page : 0 pages
File Size : 50,8 Mb
Release : 2024-08-20
Category : Computers
ISBN : 1032622601

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Deep Learning in Biomedical Signal and Medical Imaging by Ngangbam Herojit Singh,Utku Kose,Sarada Prasad Gochhayat Pdf

This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, and image processing perspectives. Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimer, Brain Tumor, Skin Cancer, Breast Cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of Artificial Intelligence (AI), Machine Learning (ML, ) and Deep CNN with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics.

Advances in Deep Learning for Medical Image Analysis

Archana Mire,Vinayak Elangovan,Shailaja Patil
Advances in Deep Learning for Medical Image Analysis Book PDF

Author : Archana Mire,Vinayak Elangovan,Shailaja Patil
Publisher : CRC Press
Page : 168 pages
File Size : 43,8 Mb
Release : 2022-04-28
Category : Technology & Engineering
ISBN : 9781000575958

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Advances in Deep Learning for Medical Image Analysis by Archana Mire,Vinayak Elangovan,Shailaja Patil Pdf

This reference text introduces the classical probabilistic model, deep learning, and big data techniques for improving medical imaging and detecting various diseases. The text addresses a wide variety of application areas in medical imaging where deep learning techniques provide solutions with lesser human intervention and reduced time. It comprehensively covers important machine learning for signal analysis, deep learning techniques for cancer detection, diabetic cases, skin image analysis, Alzheimer’s disease detection, coronary disease detection, medical image forensic, fetal anomaly detection, and plant phytology. The text will serve as a useful text for graduate students and academic researchers in the fields of electronics engineering, computer science, biomedical engineering, and electrical engineering.

Biomedical Signal Analysis

Fabian J. Theis,Anke Meyer-Bäse
Biomedical Signal Analysis Book PDF

Author : Fabian J. Theis,Anke Meyer-Bäse
Publisher : MIT Press
Page : 438 pages
File Size : 44,5 Mb
Release : 2010
Category : Computers
ISBN : 9780262013284

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Biomedical Signal Analysis by Fabian J. Theis,Anke Meyer-Bäse Pdf

A comprehensive introduction to innovative methods in the field of biomedical signal analysis, covering both theory and practice. Biomedical signal analysis has become one of the most important visualization and interpretation methods in biology and medicine. Many new and powerful instruments for detecting, storing, transmitting, analyzing, and displaying images have been developed in recent years, allowing scientists and physicians to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. This book offers an overview of a range of proven and new methods, discussing both theoretical and practical aspects of biomedical signal analysis and interpretation.After an introduction to the topic and a survey of several processing and imaging techniques, the book describes a broad range of methods, including continuous and discrete Fourier transforms, independent component analysis (ICA), dependent component analysis, neural networks, and fuzzy logic methods. The book then discusses applications of these theoretical tools to practical problems in everyday biosignal processing, considering such subjects as exploratory data analysis and low-frequency connectivity analysis in fMRI, MRI signal processing including lesion detection in breast MRI, dynamic cerebral contrast-enhanced perfusion MRI, skin lesion classification, and microscopic slice image processing and automatic labeling. Biomedical Signal Analysis can be used as a text or professional reference. Part I, on methods, forms a self-contained text, with exercises and other learning aids, for upper-level undergraduate or graduate-level students. Researchers or graduate students in systems biology, genomic signal processing, and computer-assisted radiology will find both parts I and II (on applications) a valuable handbook.

Classification and Clustering in Biomedical Signal Processing

Dey, Nilanjan
Classification and Clustering in Biomedical Signal Processing Book PDF

Author : Dey, Nilanjan
Publisher : IGI Global
Page : 463 pages
File Size : 54,8 Mb
Release : 2016-04-07
Category : Technology & Engineering
ISBN : 9781522501411

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Classification and Clustering in Biomedical Signal Processing by Dey, Nilanjan Pdf

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.

Machine Learning and Medical Imaging

Guorong Wu,Dinggang Shen,Mert Sabuncu
Machine Learning and Medical Imaging Book PDF

Author : Guorong Wu,Dinggang Shen,Mert Sabuncu
Publisher : Academic Press
Page : 512 pages
File Size : 53,7 Mb
Release : 2016-08-11
Category : Technology & Engineering
ISBN : 9780128041147

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Machine Learning and Medical Imaging by Guorong Wu,Dinggang Shen,Mert Sabuncu Pdf

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians. Demonstrates the application of cutting-edge machine learning techniques to medical imaging problems Covers an array of medical imaging applications including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics Features self-contained chapters with a thorough literature review Assesses the development of future machine learning techniques and the further application of existing techniques

Machine Learning in Medical Imaging

Kenji Suzuki,Fei Wang,Dinggang Shen,Pingkun Yan
Machine Learning in Medical Imaging Book PDF

Author : Kenji Suzuki,Fei Wang,Dinggang Shen,Pingkun Yan
Publisher : Springer
Page : 371 pages
File Size : 54,5 Mb
Release : 2011-09-25
Category : Computers
ISBN : 9783642243196

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Machine Learning in Medical Imaging by Kenji Suzuki,Fei Wang,Dinggang Shen,Pingkun Yan Pdf

This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning in Medical Imaging, MLMI 2011, held in conjunction with MICCAI 2011, in Toronto, Canada, in September 2011. The 44 revised full papers presented were carefully reviewed and selected from 74 submissions. The papers focus on major trends in machine learning in medical imaging aiming to identify new cutting-edge techniques and their use in medical imaging.

Signal Processing and Machine Learning for Biomedical Big Data

Ervin Sejdic,Tiago H. Falk
Signal Processing and Machine Learning for Biomedical Big Data Book PDF

Author : Ervin Sejdic,Tiago H. Falk
Publisher : CRC Press
Page : 624 pages
File Size : 41,5 Mb
Release : 2018-07-04
Category : Medical
ISBN : 9781498773461

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Signal Processing and Machine Learning for Biomedical Big Data by Ervin Sejdic,Tiago H. Falk Pdf

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.

Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing

Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing Book PDF

Author : Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Publisher : CRC Press
Page : 215 pages
File Size : 52,5 Mb
Release : 2020-12-22
Category : Medical
ISBN : 9781000337075

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Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi Pdf

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Deep Learning for Medical Image Analysis

S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Deep Learning for Medical Image Analysis Book PDF

Author : S. Kevin Zhou,Hayit Greenspan,Dinggang Shen
Publisher : Academic Press
Page : 544 pages
File Size : 44,8 Mb
Release : 2023-12-01
Category : Computers
ISBN : 9780323858885

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Deep Learning for Medical Image Analysis by S. Kevin Zhou,Hayit Greenspan,Dinggang Shen Pdf

Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache

Biomedical Signal and Image Processing with Artificial Intelligence

Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor
Biomedical Signal and Image Processing with Artificial Intelligence Book PDF

Author : Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor
Publisher : Springer Nature
Page : 423 pages
File Size : 43,9 Mb
Release : 2023-01-09
Category : Technology & Engineering
ISBN : 9783031158162

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Biomedical Signal and Image Processing with Artificial Intelligence by Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor Pdf

This book focuses on advanced techniques used for feature extraction, analysis, recognition, and classification in the area of biomedical signal and image processing. Contributions cover all aspects of artificial intelligence, machine learning, and deep learning in the field of biomedical signal and image processing using novel and unexplored techniques and methodologies. The book covers recent developments in both medical images and signals analyzed by artificial intelligence techniques. The authors also cover topics related to development based artificial intelligence, which includes machine learning, neural networks, and deep learning. This book will provide a platform for researchers who are working in the area of artificial intelligence for biomedical applications. Provides insights into medical signal and image analysis using artificial intelligence; Includes novel and recent trends of decision support system for medical research; Outlines employment of evolutionary algorithms for biomedical data, big data analysis for medical databases, and reliability, opportunities, and challenges in clinical data.