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Ai And Machine Learning Paradigms For Health Monitoring System
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Book Synopsis AI and Machine Learning Paradigms for Health Monitoring System by : Hasmat Malik
Download or read book AI and Machine Learning Paradigms for Health Monitoring System written by Hasmat Malik and published by Springer Nature. This book was released on 2021-02-14 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques. The first part covers AI, machine learning and data analytics tools and techniques and their applications to the class of several hospital and health real-life problems. In the later part, the applications of AI, ML and data analytics shall be covered over the wide variety of applications in hospital, health, engineering and/or applied sciences such as the clinical services, medical image analysis, management support, quality analysis, bioinformatics, device analysis and operations. The book presents knowledge of experts in the form of chapters with the objective to introduce the theme of intelligent data analytics and discusses associated theoretical applications. At last, it presents simulation codes for the problems included in the book for better understanding for beginners.
Book Synopsis Deep Learning and IoT in Healthcare Systems by : Krishna Kant Singh
Download or read book Deep Learning and IoT in Healthcare Systems written by Krishna Kant Singh and published by CRC Press. This book was released on 2021-12-15 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume discusses the applications and challenges of deep learning and the internet of things for applications in healthcare. It describes deep learning techniques in conjunction with IoT used by practitioners and researchers worldwide. The authors explore the convergence of IoT and deep learning to enable things to communicate, share information, and coordinate decisions. The book includes deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. Chapters look at assistive devices in healthcare, alerting and detection devices, energy efficiency in using IoT, data mining for gathering health information for individuals with autism, IoT for mobile applications, and more. The text also offers mathematical and conceptual background that presents the latest technology as well as a selection of case studies.
Book Synopsis Machine Learning and Artificial Intelligence in Healthcare Systems by : Tawseef Ayoub Shaikh
Download or read book Machine Learning and Artificial Intelligence in Healthcare Systems written by Tawseef Ayoub Shaikh and published by CRC Press. This book was released on 2022-02-22 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment. Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting user social behavior (known as sentiment analysis for healthcare-related purposes) round out the diverse array of topics this reference book covers. Contributions from experts in the field, this book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.
Book Synopsis Artificial Intelligence for Health 4.0: Challenges and Applications by : Rishabha Malviya
Download or read book Artificial Intelligence for Health 4.0: Challenges and Applications written by Rishabha Malviya and published by CRC Press. This book was released on 2023-03-10 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare is one of the major success stories of our times. Medical science has improved rapidly, raising life expectancy around the world. However, as longevity increases, healthcare systems face growing demands for their services, rising costs, and a workforce that is struggling to meet the needs of its patients. Healthcare is one of the most critical sectors in the broader landscape of big data because of its fundamental role in a productive, thriving society. Building on automation, artificial intelligence (AI) has the potential to revolutionize healthcare and help address some of the challenges set out above. The application of AI to healthcare data can literally be a matter of life and death. AI can assist doctors, nurses, and other healthcare workers in their daily work. AI in healthcare can enhance preventive care and quality of life, produce more accurate diagnoses and treatment plans, and lead to better patient outcomes overall. This book gives insights into the latest developments of applications of AI in biomedicine, including disease diagnostics, pharmaceutical processing, patient care and monitoring, biomedical information, and biomedical research. It also presents an outline of the recent breakthroughs in the application of AI in healthcare, describes a roadmap to building effective, reliable, and safe AI systems, and discusses the possible future direction of AI augmented healthcare systems. AI has countless applications in healthcare. Whether it’s being used to discover links between genetic codes, to power surgical robots or even to maximize hospital efficiency; AI has been a boon to the healthcare industry.
Book Synopsis Machine Learning and Analytics in Healthcare Systems by : Himani Bansal
Download or read book Machine Learning and Analytics in Healthcare Systems written by Himani Bansal and published by CRC Press. This book was released on 2021-06-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bridges the gap between engineering and medicine in combining the design and problem solving skills of engineering with health sciences Explores real-world case studies in machine learning and healthcare analytics Presents a detailed exploration of applications of machine learning in healthcare systems Provides readers with how the industry avoids some of the consequences of old methods of data sharing strategies Offers readers multiple perspectives on a variety of disciplines
Book Synopsis Artificial Intelligence in Healthcare by : Adam Bohr
Download or read book Artificial Intelligence in Healthcare written by Adam Bohr and published by Academic Press. This book was released on 2020-06-21 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data
Book Synopsis Machine Learning in Healthcare by : Bikesh Kumar Singh
Download or read book Machine Learning in Healthcare written by Bikesh Kumar Singh and published by CRC Press. This book was released on 2022-02-17 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) and machine learning (ML) techniques play an important role in our daily lives by enhancing predictions and decision-making for the public in several fields such as financial services, real estate business, consumer goods, social media, etc. Despite several studies that have proved the efficacy of AI/ML tools in providing improved healthcare solutions, it has not gained the trust of health-care practitioners and medical scientists. This is due to poor reporting of the technology, variability in medical data, small datasets, and lack of standard guidelines for application of AI. Therefore, the development of new AI/ML tools for various domains of medicine is an ongoing field of research. Machine Learning in Healthcare: Fundamentals and Recent Applications discusses how to build various ML algorithms and how they can be applied to improve healthcare systems. Healthcare applications of AI are innumerable: medical data analysis, early detection and diagnosis of disease, providing objective-based evidence to reduce human errors, curtailing inter- and intra-observer errors, risk identification and interventions for healthcare management, real-time health monitoring, assisting clinicians and patients for selecting appropriate medications, and evaluating drug responses. Extensive demonstrations and discussion on the various principles of machine learning and its application in healthcare is provided, along with solved examples and exercises. This text is ideal for readers interested in machine learning without any background knowledge and looking to implement machine-learning models for healthcare systems.
Book Synopsis Machine Learning with Health Care Perspective by : Vishal Jain
Download or read book Machine Learning with Health Care Perspective written by Vishal Jain and published by Springer Nature. This book was released on 2020-03-09 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.
Book Synopsis System Design for Epidemics Using Machine Learning and Deep Learning by : G. R. Kanagachidambaresan
Download or read book System Design for Epidemics Using Machine Learning and Deep Learning written by G. R. Kanagachidambaresan and published by Springer Nature. This book was released on 2023-02-01 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.
Book Synopsis Machine Learning and the Internet of Medical Things in Healthcare by : Krishna Kant Singh
Download or read book Machine Learning and the Internet of Medical Things in Healthcare written by Krishna Kant Singh and published by Academic Press. This book was released on 2021-04-14 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks. Provides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies
Book Synopsis AI and IoT-based Intelligent Health Care & Sanitation by : Shashank Awasthi
Download or read book AI and IoT-based Intelligent Health Care & Sanitation written by Shashank Awasthi and published by Bentham Science Publishers. This book was released on 2023-04-13 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to provide a deeper understanding of the synergistic impact of Artificial intelligence (AI) and the Internet of Things (IoT) for disease detection. It presents a collection of topics designed to explain methods to detect different diseases in humans and plants. Chapters are edited by experts in IT and machine learning, and are structured to make the volume accessible to a wide range of readers. Key Features: - 17 Chapters present information about the applications of AI and IoT in clinical medicine and plant biology - Provides examples of algorithms for heart diseases, Alzheimer’s disease, cancer, pneumonia and more - Includes techniques to detect plant disease - Includes information about the application of machine learning in specific imaging modalities - Highlights the use of a variety of advanced Deep learning techniques like Mask R-CNN - Each chapter provides an introduction and literature review and the relevant protocols to follow The book is an informative guide for data and computer scientists working to improve disease detection techniques in medical and life sciences research. It also serves as a reference for engineers working in the healthcare delivery sector.
Book Synopsis Intelligent Healthcare by : Surbhi Bhatia
Download or read book Intelligent Healthcare written by Surbhi Bhatia and published by Springer Nature. This book was released on 2021-07-02 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book fosters a scientific debate for sophisticated approaches and cognitive technologies (such as deep learning, machine learning and advanced analytics) for enhanced healthcare services in light of the tremendous scope in the future of intelligent systems for healthcare. The authors discuss the proliferation of huge data sources (e.g. genomes, electronic health records (EHRs), mobile diagnostics, and wearable devices) and breakthroughs in artificial intelligence applications, which have unlocked the doors for diagnosing and treating multitudes of rare diseases. The contributors show how the widespread adoption of intelligent health based systems could help overcome challenges, such as shortages of staff and supplies, accessibility barriers, lack of awareness on certain health issues, identification of patient needs, and early detection and diagnosis of illnesses. This book is a small yet significant step towards exploring recent advances, disseminating state-of-the-art techniques and deploying novel technologies in intelligent healthcare services and applications. Describes the advances of computing methodologies for life and medical science data; Presents applications of artificial intelligence in healthcare along with case studies and datasets; Provides an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.
Book Synopsis Digital Health Transformation with Blockchain and Artificial Intelligence by : Chinmay Chakraborty
Download or read book Digital Health Transformation with Blockchain and Artificial Intelligence written by Chinmay Chakraborty and published by CRC Press. This book was released on 2022-05-10 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book Digital Health Transformation with Blockchain and Artificial Intelligence covers the global digital revolution in the field of healthcare sector. The population has been overcoming the COVID-19 period; therefore, we need to establish intelligent digital healthcare systems using various emerging technologies like Blockchain and Artificial Intelligence. Internet of Medical Things is the technological revolution that has included the element of "smartness" in the healthcare industry and also identifying, monitoring, and informing service providers about the patient’s clinical information with faster delivery of care services. This book highlights the important issues i.e. (a) How Internet of things can be integrated with the healthcare ecosystem for better diagnostics, monitoring, and treatment of the patients, (b) Artificial Intelligence for predictive and preventive healthcare systems, (c) Blockchain for managing healthcare data to provide transparency, security, and distributed storage, and (d) Effective remote diagnostics and telemedicine approach for developing smart care. The book encompasses chapters belong to the blockchain, Artificial Intelligence, and Big health data technologies. Features: Blockchain and internet of things in healthcare systems Secure Digital Health Data Management in Internet of Things Public Perception towards AI-Driven Healthcare Security, privacy issues and challenges in adoption of smart digital healthcare Big data analytics and Internet of things in the pandemic era Clinical challenges for digital health revolution Artificial intelligence for advanced healthcare Future Trajectory of Healthcare with Artificial Intelligence 9 Parkinson disease pre-diagnosis using smart technologies Emerging technologies to combat the COVID-19 Machine Learning and Internet of Things in Digital Health Transformation Effective Remote Healthcare and Telemedicine Approaches Legal implication of blockchain technology in public health This Book on "Digital Health Transformation with Blockchain and Artificial Intelligence" aims at promoting and facilitating exchanges of research knowledge and findings across different disciplines on the design and investigation of secured healthcare data analytics. It can also be used as a textbook for a Masters course in security and biomedical engineering. This book will also present new methods for the medical data analytics, blockchain technology, and diagnosis of different diseases to improve the quality of life in general, and better integration into digital healthcare.
Book Synopsis Artificial Intelligence and Machine Learning in Public Healthcare by : KC Santosh
Download or read book Artificial Intelligence and Machine Learning in Public Healthcare written by KC Santosh and published by Springer Nature. This book was released on 2022-01-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors into account: open public health issues and common AI solutions (with multiple case studies, such as TB and SARS: COVID-19), AI in sustainable health care, AI in precision medicine and data privacy issues. Public health requires special attention as it drives economy and education system. COVID-19 is an example—a truly infectious disease outbreak. The vision of WHO is to create public health services that can deal with abovementioned crucial challenges by focusing on the following elements: health protection, disease prevention and health promotion. For these issues, in the big data analytics era, AI and ML tools/techniques have potential to improve public health (e.g., existing healthcare solutions and wellness services). In other words, they have proved to be valuable tools not only to analyze/diagnose pathology but also to accelerate decision-making procedure especially when we consider resource-constrained regions.
Book Synopsis Intelligent Sensor Node-Based Systems by : Anamika Ahirwar
Download or read book Intelligent Sensor Node-Based Systems written by Anamika Ahirwar and published by CRC Press. This book was released on 2023-10-06 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume covers the fusion of IoT and wireless communication technology for real-life applications. It discusses the current developments, trends, and latest usage of technology in wireless sensor networks (WSNs) and IoT, which offer improvement in many areas, including in enabling smart homes, in agricultural systems, for security systems, for university monitoring systems, and more. The volume also provides a theoretical analysis and discussion of the factors influencing smart sensing, exploring the state-of-the-art IoT elements that are designed to be analogous to WSNs. It looks at advancements in IoT systems along with a two-way usage with wireless sensor networks that span the gap between the physical and virtual worlds, leading to a hyperconnected society where devices are not only used to exchange data but also are smart devices with more capabilities. The chapters reveal how these technologies are used in smart homes, for intelligent sensor-based cognitive radio networks, for different techniques for data fusion, for the synthesis and fabrication of nanosensor devices for monitoring agricultural nutrient levels, and more. Furthermore, the fake user problems in WSNs are also investigated with a note on the current trends and the newer trends to come in near future.
Book Synopsis Machine Learning and AI for Healthcare by : Arjun Panesar
Download or read book Machine Learning and AI for Healthcare written by Arjun Panesar and published by Apress. This book was released on 2019-02-04 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges. You’ll discover the ethical implications of healthcare data analytics and the future of AI in population and patient health optimization. You’ll also create a machine learning model, evaluate performance and operationalize its outcomes within your organization. Machine Learning and AI for Healthcare provides techniques on how to apply machine learning within your organization and evaluate the efficacy, suitability, and efficiency of AI applications. These are illustrated through leading case studies, including how chronic disease is being redefined through patient-led data learning and the Internet of Things. What You'll LearnGain a deeper understanding of key machine learning algorithms and their use and implementation within wider healthcare Implement machine learning systems, such as speech recognition and enhanced deep learning/AI Select learning methods/algorithms and tuning for use in healthcare Recognize and prepare for the future of artificial intelligence in healthcare through best practices, feedback loops and intelligent agentsWho This Book Is For Health care professionals interested in how machine learning can be used to develop health intelligence – with the aim of improving patient health, population health and facilitating significant care-payer cost savings.
Book Synopsis Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease by : Roy, Manikant
Download or read book Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease written by Roy, Manikant and published by IGI Global. This book was released on 2021-06-25 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.
