Extracting Insights From Digital Public Health Data Using Artificial Intelligence Volume Ii
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Extracting Insights From Digital Public Health Data Using Artificial Intelligence Volume Ii
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Author : Steven Fernandes
language : en
Publisher: Frontiers Media SA
Release Date : 2024-04-19
Extracting Insights From Digital Public Health Data Using Artificial Intelligence Volume Ii written by Steven Fernandes 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 2024-04-19 with Medical categories.
This Research Topic is a follow on from the Topic Editors' successful volume I. Artificial Intelligence (AI) has the ability to perform automated/case-based reasoning, constraint processing, deep learning, and deep reinforcement learning. Recent advancements in AI techniques and GPU (graphics processing unit) computing capabilities have made it possible to process large volumes of data and extract valuable insights within a short period. Digital public health data are enormous, and harnessing AI's power can lead to exciting and ground-breaking research. Due to the current COVID-19 pandemic, AI can assist in disease surveillance methods, infectious disease modeling, non-contact temperature screening, intelligent contact tracking, detecting social/economic factors on transmission, effective health communication and misinformation detection, identifying factors that affect the mental and emotional health of the public.
Extracting Insights From Digital Public Health Data Using Artificial Intelligence
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Author : Yu-Dong Zhang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-05
Extracting Insights From Digital Public Health Data Using Artificial Intelligence written by Yu-Dong Zhang 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 2022-12-05 with Science categories.
Data Science For Covid 19
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Author : Utku Kose
language : en
Publisher: Academic Press
Release Date : 2021-10-22
Data Science For Covid 19 written by Utku Kose and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Science categories.
Data Science for COVID-19, Volume 2: Societal and Medical Perspectives presents the most current and leading-edge research into the applications of a variety of data science techniques for the detection, mitigation, treatment and elimination of the COVID-19 virus. At this point, Cognitive Data Science is the most powerful tool for researchers to fight COVID-19. Thanks to instant data-analysis and predictive techniques, including Artificial Intelligence, Machine Learning, Deep Learning, Data Mining, and computational modeling for processing large amounts of data, recognizing patterns, modeling new techniques, and improving both research and treatment outcomes is now possible. Provides a leading-edge survey of Data Science techniques and methods for research, mitigation and the treatment of the COVID-19 virus Integrates various Data Science techniques to provide a resource for COVID-19 researchers and clinicians around the world, including the wide variety of impacts the virus is having on societies and medical practice Presents insights into innovative, data-oriented modeling and predictive techniques from COVID-19 researchers around the world, including geoprocessing and tracking, lab data analysis, and theoretical views on a variety of technical applications Includes real-world feedback and user experiences from physicians and medical staff from around the world for medical treatment perspectives, public safety policies and impacts, sociological and psychological perspectives, the effects of COVID-19 in agriculture, economies, and education, and insights on future pandemics
Digital Health Transformation With Blockchain And Artificial Intelligence
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Author : Chinmay Chakraborty
language : en
Publisher: CRC Press
Release Date : 2022-05-10
Digital Health Transformation With Blockchain And Artificial Intelligence written by Chinmay Chakraborty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-10 with Computers categories.
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.
Artificial Intelligence And Machine Learning In Public Healthcare
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Author : KC Santosh
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Artificial Intelligence And Machine Learning In Public Healthcare written by KC Santosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
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.
Transforming Healthcare With Big Data And Ai
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Author : Mingbo Gong
language : en
Publisher: IAP
Release Date : 2020-04-01
Transforming Healthcare With Big Data And Ai written by Mingbo Gong and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Computers categories.
Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Data Science For Healthcare
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Author : Sergio Consoli
language : en
Publisher: Springer
Release Date : 2019-02-23
Data Science For Healthcare written by Sergio Consoli and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-23 with Computers categories.
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
Machine Learning And Ai For Healthcare
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Author : Arjun Panesar
language : en
Publisher: Apress
Release Date : 2019-02-04
Machine Learning And Ai For Healthcare written by Arjun Panesar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-04 with Computers categories.
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.
Demystifying Big Data And Machine Learning For Healthcare
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Author : Prashant Natarajan
language : en
Publisher: CRC Press
Release Date : 2017-02-15
Demystifying Big Data And Machine Learning For Healthcare written by Prashant Natarajan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-15 with Medical categories.
Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.
Artificial Intelligence And Machine Learning In Public Healthcare
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Author : KC Santosh
language : en
Publisher:
Release Date : 2021
Artificial Intelligence And Machine Learning In Public Healthcare written by KC Santosh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
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.