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Author : Elena Tolkacheva
Publisher : Frontiers Media SA
ISBN 13 : 2832522939
Total Pages : 186 pages
Book Rating : 4.8/5 (325 download)
Download or read book Nonlinear analysis and machine learning in cardiology written by Elena Tolkacheva and published by Frontiers Media SA. This book was released on with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Rajesh Kumar Tripathy
Publisher : Elsevier
ISBN 13 : 0443141401
Total Pages : 186 pages
Book Rating : 4.4/5 (431 download)
Download or read book Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing written by Rajesh Kumar Tripathy and published by Elsevier. This book was released on 2024-06-17 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular data analysis. Topics in this book include machine learning methods such as supervised learning, unsupervised learning, semi-supervised learning, and meta-learning combined with different signal processing techniques such as multivariate data analysis, time-frequency analysis, multiscale analysis, and feature extraction techniques for the detection of cardiovascular diseases, heart valve disorders, hypertension, and activity monitoring using ECG, PPG, and PCG signals. In addition, this book also includes the applications of digital signal processing (time-frequency analysis, multiscale decomposition, feature extraction, non-linear analysis, and transform domain methods), machine learning and deep learning (convolutional neural network (CNN), recurrent neural network (RNN), transformer and attention-based models, etc.) techniques for the analysis of cardiac signals. The interpretable machine learning and deep learning models combined with signal processing for cardiovascular data analysis are also covered. Provides details regarding the application of various signal processing and machine learning-based methods for cardiovascular signal analysis Covers methodologies as well as experimental results and studies Helps readers understand the use of different cardiac signals such as ECG, PCG, and PPG for the automated detection of heart ailments and other related biomedical applications
Author : Nilanjan Dey
Publisher : Academic Press
ISBN 13 : 012816087X
Total Pages : 348 pages
Book Rating : 4.1/5 (281 download)
Download or read book Machine Learning in Bio-Signal Analysis and Diagnostic Imaging written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Alfonso Limon
Publisher : Elsevier
ISBN 13 : 032390629X
Total Pages : 542 pages
Book Rating : 4.3/5 (239 download)
Download or read book Intelligence-Based Cardiology and Cardiac Surgery written by Alfonso Limon and published by Elsevier. This book was released on 2023-09-19 with total page 542 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligence-Based Cardiology and Cardiac Surgery: Artificial Intelligence and Human Cognition in Cardiovascular Medicine provides a comprehensive survey of artificial intelligence concepts and methodologies with real-life applications in cardiovascular medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and data science domains. The book's content consists of basic concepts of artificial intelligence and human cognition applications in cardiology and cardiac surgery. This portfolio ranges from big data, machine and deep learning, cognitive computing and natural language processing in cardiac disease states such as heart failure, hypertension and pediatric heart care. The book narrows the knowledge and expertise chasm between the data scientists, cardiologists and cardiac surgeons, inspiring clinicians to embrace artificial intelligence methodologies, educate data scientists about the medical ecosystem, and create a transformational paradigm for healthcare and medicine. Covers a wide range of relevant topics from real-world data, large language models, and supervised machine learning to deep reinforcement and federated learning Presents artificial intelligence concepts and their applications in many areas in an easy-to-understand format accessible to clinicians and data scientists Discusses using artificial intelligence and related technologies with cardiology and cardiac surgery in a myriad of venues and situations Delineates the necessary elements for successfully implementing artificial intelligence in cardiovascular medicine for improved patient outcomes Presents the regulatory, ethical, legal, and financial issues embedded in artificial intelligence applications in cardiology
Author : Riccardo Barbieri
Publisher : Springer
ISBN 13 : 3319587099
Total Pages : 535 pages
Book Rating : 4.3/5 (195 download)
Download or read book Complexity and Nonlinearity in Cardiovascular Signals written by Riccardo Barbieri and published by Springer. This book was released on 2017-08-09 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the latest advances in complex and nonlinear cardiovascular physiology aimed at obtaining reliable, effective markers for the assessment of heartbeat, respiratory, and blood pressure dynamics. The chapters describe in detail methods that have been previously defined in theoretical physics such as entropy, multifractal spectra, and Lyapunov exponents, contextualized within physiological dynamics of cardiovascular control, including autonomic nervous system activity. Additionally, the book discusses several application scenarios of these methods. The text critically reviews the current state-of-the-art research in the field that has led to the description of dedicated experimental protocols and ad-hoc models of complex physiology. This text is ideal for biomedical engineers, physiologists, and neuroscientists. This book also: Expertly reviews cutting-edge research, such as recent advances in measuring complexity, nonlinearity, and information-theoretic concepts applied to coupled dynamical systems Comprehensively describes applications of analytic technique to clinical scenarios such as heart failure, depression and mental disorders, atrial fibrillation, acute brain lesions, and more Broadens readers' understanding of cardiovascular signals, heart rate complexity, heart rate variability, and nonlinear analysis
Author : Subhi J. Al'Aref
Publisher : Academic Press
ISBN 13 : 0128202742
Total Pages : 456 pages
Book Rating : 4.1/5 (282 download)
Download or read book Machine Learning in Cardiovascular Medicine written by Subhi J. Al'Aref and published by Academic Press. This book was released on 2020-11-20 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 its computational power to streamline workflow and improve patient care. It is suitable for both clinicians and engineers; providing a template for clinicians to understand areas of application of machine learning within cardiovascular research; and assist computer scientists and engineers in evaluating current and future impact of machine learning on cardiovascular medicine. Provides an overview of machine learning, both for a clinical and engineering audience Summarize recent advances in both cardiovascular medicine and artificial intelligence Discusses the advantages of using machine learning for outcomes research and image processing Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach
Author : Swati V. Shinde
Publisher : CRC Press
ISBN 13 : 100089620X
Total Pages : 459 pages
Book Rating : 4.0/5 (8 download)
Download or read book Applied Artificial Intelligence written by Swati V. Shinde and published by CRC Press. This book was released on 2023-09-29 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the advancements and future challenges in biomedical application developments using breakthrough technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Signal Processing. It will also contribute to biosensors and secure systems,and related research. Applied Artificial Intelligence: A Biomedical Perspective begins by detailing recent trends and challenges of applied artificial intelligence in biomedical systems. Part I of the book presents the technological background of the book in terms of applied artificial intelligence in the biomedical domain. Part II demonstrates the recent advancements in automated medical image analysis that have opened ample research opportunities in the applications of deep learning to different diseases. Part III focuses on the use of cyberphysical systems that facilitates computing anywhere by using medical IoT and biosensors and the numerous applications of this technology in the healthcare domain. Part IV describes the different signal processing applications in the healthcare domain. It also includes the prediction of some human diseases based on the inputs in signal format. Part V highlights the scope and applications of biosensors and security aspects of biomedical images. The book will be beneficial to the researchers, industry persons, faculty, and students working in biomedical applications of computer science and electronics engineering. It will also be a useful resource for teaching courses like AI/ML, medical IoT, signal processing, biomedical engineering, and medical image analysis.
Author : César A. González Díaz
Publisher : Springer Nature
ISBN 13 : 3030306488
Total Pages : 1518 pages
Book Rating : 4.0/5 (33 download)
Download or read book VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering written by César A. González Díaz and published by Springer Nature. This book was released on 2019-09-30 with total page 1518 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the joint proceedings of the VIII Latin American Conference on Biomedical Engineering (CLAIB 2019) and the XLII National Conference on Biomedical Engineering (CNIB 2019). It reports on the latest findings and technological outcomes in the biomedical engineering field. Topics include: biomedical signal and image processing; biosensors, bioinstrumentation and micro-nanotechnologies; biomaterials and tissue engineering. Advances in biomechanics, biorobotics, neurorehabilitation, medical physics and clinical engineering are also discussed. A special emphasis is given to practice-oriented research and to the implementation of new technologies in clinical settings. The book provides academics and professionals with extensive knowledge on and a timely snapshot of cutting-edge research and developments in the field of biomedical engineering.
Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128176733
Total Pages : 456 pages
Book Rating : 4.1/5 (281 download)
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
Author : Nicolas Duchateau
Publisher : Springer Nature
ISBN 13 : 3031050711
Total Pages : 220 pages
Book Rating : 4.0/5 (31 download)
Download or read book AI and Big Data in Cardiology written by Nicolas Duchateau and published by Springer Nature. This book was released on 2023-05-04 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a detailed technical overview of the use and applications of artificial intelligence (AI), machine learning and big data in cardiology. Recent technological advancements in these fields mean that there is significant gain to be had in applying these methodologies into day-to-day clinical practice. Chapters feature detailed technical reviews and highlight key current challenges and limitations, along with the available techniques to address them for each topic covered. Sample data sets are also included to provide hands-on tutorials for readers using Python-based Jupyter notebooks, and are based upon real-world examples to ensure the reader can develop their confidence in applying these techniques to solve everyday clinical problems. Artificial Intelligence and Big Data in Cardiology systematically describes and technically reviews the latest applications of AI and big data within cardiology. It is ideal for use by the trainee and practicing cardiologist and informatician seeking an up-to-date resource on the topic with which to aid them in developing a thorough understanding of both basic concepts and recent advances in the field.
Author : Takashi Washio
Publisher : Springer
ISBN 13 : 3540770186
Total Pages : 688 pages
Book Rating : 4.5/5 (47 download)
Download or read book Emerging Technologies in Knowledge Discovery and Data Mining written by Takashi Washio and published by Springer. This book was released on 2007-11-27 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-proceedings of three workshops and an industrial track held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007. The 62 revised full papers presented together with an overview article to each workshop were carefully reviewed and selected from 355 submissions.
Author : Eugenio Picano
Publisher : Springer Nature
ISBN 13 : 3031310624
Total Pages : 674 pages
Book Rating : 4.0/5 (313 download)
Download or read book Stress Echocardiography written by Eugenio Picano and published by Springer Nature. This book was released on 2023-10-19 with total page 674 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the seventh edition of a long-selling book (first edition 1991) that was translated into Italian, French, Chinese, Portuguese, Spanish, English. In the last ten years, stress echocardiography has exploded in its breadth and variety of applications. From a one-fits-all approach (wall motion by 2D-echo in the patient with known or suspected coronary artery disease), the field has progressed to an omnivorous, next-generation laboratory employing a variety of technologies (from M-Mode to 2D, from pulsed, continuous, color and tissue Doppler to lung ultrasound) on patients covering the entire spectrum of severity (from elite athletes to patients with end-stage heart failure) and ages (from children with congenital heart disease to the elderly with aortic stenosis). This new edition is enriched with over 300 figures, 150 tables and video-clips. In a societal and economic climate of increasing pressure for appropriate, justified and optimized imaging, stress echocardiography offers the great advantages of being radiation-free, relatively low cost, with minimal environmental impact, and with a staggering versatility: we can get more (information) with less (cost and risk). The volume will be a tremendous aid to current best practices for all health operators who intend to use stress echocardiography and ultrasound for diagnosis and guidance of optimal management in their patients.
Author : Basant Agarwal
Publisher : Academic Press
ISBN 13 : 0128190620
Total Pages : 367 pages
Book Rating : 4.1/5 (281 download)
Download or read book Deep Learning Techniques for Biomedical and Health Informatics written by Basant Agarwal and published by Academic Press. This book was released on 2020-01-14 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis
Author : Nenad Filipovic
Publisher : Academic Press
ISBN 13 : 0128242299
Total Pages : 314 pages
Book Rating : 4.1/5 (282 download)
Download or read book Cardiovascular and Respiratory Bioengineering written by Nenad Filipovic and published by Academic Press. This book was released on 2022-05-12 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory systems that help develop bioengineered solutions. The book demonstrates how these technologies can be utilized in order to tackle diseases and medical issues. It provides practical guidance on how a bioengineering or medical problem can be modeled, along with which computational models can be used. Topics include computer modeling of Purkinje fibers with different electrical potential applied, modeling of cardiomyopathies caused by sarcomeric gene mutations, altered sarcomere function, perturbations in intracellular ion homeostasis, impaired myocardial energetics at reduced costs, and more. The book also discusses blood flow through deformable blood vessels in human aorta, abdominal aortic aneurysm, carotid artery, coronary artery and plaque formation, along with content on stent deployment modeling and stent design and optimization techniques. Features practical applications of cardiovascular and respiratory technology to counteract diseases Includes detailed steps for the modeling of cardiovascular and respiratory systems Explores a range of different modeling methods, including computational modeling, predictive modeling and multi-scale modeling Covers biological processes and biomechanics relevant to cardiovascular and respiratory bioengineering
Author : Antoniya Georgieva
Publisher : Frontiers Media SA
ISBN 13 : 2832502393
Total Pages : 196 pages
Book Rating : 4.8/5 (325 download)
Download or read book Fetal-Maternal Monitoring in the Age of Artificial Intelligence and Computer-Aided Decision Support: A Multidisciplinary Perspective written by Antoniya Georgieva and published by Frontiers Media SA. This book was released on 2022-10-14 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jieyun Bai
Publisher : Frontiers Media SA
ISBN 13 : 2832533876
Total Pages : 379 pages
Book Rating : 4.8/5 (325 download)
Download or read book Diagnosis, Monitoring, and Treatment of Heart Rhythm: New Insights and Novel Computational Methods written by Jieyun Bai and published by Frontiers Media SA. This book was released on 2023-09-13 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ervin Sejdic
Publisher : CRC Press
ISBN 13 : 149877346X
Total Pages : 624 pages
Book Rating : 4.4/5 (987 download)
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.
