Signal Processing Driven Machine Learning Techniques For Cardiovascular Data Processing
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Signal Processing Driven Machine Learning Techniques For Cardiovascular Data Processing
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Author : Rajesh Kumar Tripathy
language : en
Publisher: Elsevier
Release Date : 2024-06-12
Signal Processing Driven Machine Learning Techniques For Cardiovascular Data Processing written by Rajesh Kumar Tripathy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-12 with Computers categories.
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
Cutting Edge Diagnostic Technologies In Cardiovascular Diseases
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Author : Haipeng Liu
language : en
Publisher: CRC Press
Release Date : 2025-06-23
Cutting Edge Diagnostic Technologies In Cardiovascular Diseases written by Haipeng Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-23 with Technology & Engineering categories.
This book provides a comprehensive overview of cutting-edge technologies in the diagnosis of multiple cardiovascular disease. Readers will understand technical advancements and research gaps, which will help them to optimize the design of algorithms and devices. Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases: Towards Data-Driven Smart Healthcare provides details on the adoption and implementation of advanced diagnostic techniques in different clinical settings, including population screening, clinical diagnosis, risk prediction, data-driven diagnosis, and remote healthcare monitoring. It also covers various cardiovascular diseases, from the macrovascular to microvascular levels, where early and accurate diagnosis is a high clinical need, for example, stroke, intracranial atherosclerosis, coronary artery disease, and microvascular dysfunction. The book is a practical guide with case studies, and the authors cover a wide range of cutting-edge diagnostic techniques, including artificial intelligence, radiological imaging, wearable sensors, genetic biomarkers, and multi-omics data integration. It summarizes the potentials, challenges, and ethical concerns in the implementation of these techniques under current clinical settings. It also discusses the future directions and perspectives for next-generation diagnostics based on AI-enhanced multimodal data fusion. This book targets a mixed audience of data scientists, engineers, clinicians, researchers, academics, and students interested in cutting-edge technologies, methodologies, and practices in the diagnostics of cardiovascular diseases to resolve the challenging gaps in healthcare and clinical applications.
Ai Driven Biomedical Data Science And Signal Processing
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Author : NISHIT AGARWAL PROF.(DR.) ARVIND KUMAR
language : en
Publisher: DeepMisti Publication
Release Date : 2024-12-22
Ai Driven Biomedical Data Science And Signal Processing written by NISHIT AGARWAL PROF.(DR.) ARVIND KUMAR and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-22 with Computers categories.
In the age of rapid technological advancements, the fusion of artificial intelligence and biomedical data science has revolutionized how we approach healthcare and life sciences. This book, AI-Driven Biomedical Data Science and Signal Processing, is designed to illuminate the transformative potential of AI in unraveling complex biomedical challenges and optimizing signal processing for medical applications. Our objective is to bridge the gap between cutting-edge AI techniques and their practical applications in the biomedical domain, equipping readers with the knowledge and tools needed to excel in this evolving field. This book offers a comprehensive exploration of the methodologies, frameworks, and technologies that drive innovation in biomedical data analysis and signal interpretation. From fundamental concepts to sophisticated applications, we delve into essential strategies for processing, analyzing, and interpreting diverse biomedical datasets. Whether you are a student, researcher, healthcare professional, or industry expert, this book is tailored to provide actionable insights and a deep understanding of the intersection between AI and biomedical science. In crafting this book, we have combined state-of-the-art research with practical case studies to provide a balanced perspective that is both theoretical and application-focused. The chapters are meticulously structured to cover foundational topics such as AI-driven data preprocessing, feature extraction, and signal classification, as well as advanced themes like deep learning for medical imaging, predictive modeling for healthcare outcomes, and real-time signal processing for wearable devices. Special attention is given to emerging areas such as precision medicine and AI-assisted diagnostics, ensuring the content reflects the forefront of innovation in biomedical science. We envision this book as a vital resource for those seeking to harness the power of AI in biomedical data science and signal processing. It is our sincere hope that the insights shared here will empower readers to lead the way in advancing healthcare technologies and improving patient outcomes. Thank you for joining us on this journey of discovery and innovation. Authors
Signal Processing And Machine Learning For Biomedical Big Data
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Author : Ervin Sejdic
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Signal Processing And Machine Learning For Biomedical Big Data written by Ervin Sejdic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Medical categories.
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.
Intelligence Based Cardiology And Cardiac Surgery
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Author : Anthony C. Chang
language : en
Publisher: Elsevier
Release Date : 2023-09-06
Intelligence Based Cardiology And Cardiac Surgery written by Anthony C. Chang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-06 with Science categories.
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
The Combination Of Data Driven Machine Learning Approaches And Prior Knowledge For Robust Medical Image Processing And Analysis
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Author : Jinming Duan
language : en
Publisher: Frontiers Media SA
Release Date : 2024-06-11
The Combination Of Data Driven Machine Learning Approaches And Prior Knowledge For Robust Medical Image Processing And Analysis written by Jinming Duan and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-11 with Medical categories.
With the availability of big image datasets and state-of-the-art computing hardware, data-driven machine learning approaches, particularly deep learning, have been used in numerous medical image (CT-scans, MRI, PET, SPECT, etc..) computing tasks, ranging from image reconstruction, super-resolution, segmentation, registration all the way to disease classification and survival prediction. However, training such high-precision approaches often require large amounts of data to be collected and labelled and high-capacity graphics processing units (GPUs) installed, which are resource intensive and hence not always practical. Other hurdles such as the generalization ability to unseen new data and difficulty to interpret and explain can prevent their deployment to those clinical applications which deem such abilities imperative.
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2019-03-16
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Medical categories.
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
Digital Transformation In Healthcare 5 0
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Author : Rishabha Malviya
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-05-06
Digital Transformation In Healthcare 5 0 written by Rishabha Malviya and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-06 with Computers categories.
"Digital Transformation in Healthcare 5.0: IoT, AI, and Digital Twin" provides a comprehensive overview of the integration of cutting-edge technology with healthcare, from the Fourth Industrial Revolution (4IR) to the introduction of IoT, AI, and Digital Twin technologies. This in-depth discussion of the digital revolution expanding the healthcare industry covers a wide range of topics, including digital disruption in healthcare delivery, the impact of 4IR and Health 4.0, e-health services and applications, virtual reality's impact on accessible healthcare delivery, digital twins and dietary health technologies, big data analytics in healthcare systems, machine learning models for cost-effective healthcare delivery systems, affordable healthcare with machine learning, enhanced biomedical signal processing with machine learning, and data-driven AI for information retrieval of biomedical images.
Applications Of Optimization And Machine Learning In Image Processing And Iot
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Author : Nidhi Gupta
language : en
Publisher: CRC Press
Release Date : 2023-12-01
Applications Of Optimization And Machine Learning In Image Processing And Iot written by Nidhi Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Computers categories.
- Fills a niche in the market introducing techniques in a way that is accessible to wide audience (targeting advanced UG/G audiences in particular). - Examines cutting-edge research from a global team of active researchers. - The joint focus on IoT and image processing is unique in the market.
Future Connected Technologies
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Author : Maanak Gupta
language : en
Publisher: CRC Press
Release Date : 2023-07-17
Future Connected Technologies written by Maanak Gupta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-17 with Computers categories.
The main aim of the book is to familiarize readers with the concepts of convergence of different connected and smart domains that are assisted by Cloud Computing, core technologies behind Cloud Computing, driving factors towards Cloud Computing, and security challenges and proposed solutions in Cloud Computing. The book covers not only the cloud, but also other pertinent topics such as Machine Learning, Deep Learning, IoT and Fog/Edge Computing. The last section of the book mainly focuses on the security aspects of connected technologies. The highpoints of the book is that it reviews the relation and combination of the mentioned topics, which together creates a better understanding about almost every aspect of Cloud Computing & related technologies.