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Predictive and Preventive Measures for Covid-19 Pandemic

Author: Praveen Kumar Khosla

Publisher: Springer Nature

Published: 2021-01-22

Total Pages: 335

ISBN-13: 9813342366

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This book explores the inputs with regard to individuals and companies who have developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, etc., that can be leveraged for strengthening the fight against coronavirus. It focuses on technology solutions to stop Covid-19 outbreak and mitigate the risk. The book contains innovative ideas from active researchers who are presently working to find solutions, and they give insights to other researchers to explore the innovative methods and predictive modeling techniques. The novel applications and techniques of established technologies like artificial intelligence (AI), Internet of things (IoT), big data, computer vision and machine learning are discussed to fight the spread of this disease, Covid-19. This pandemic has triggered an unprecedented demand for digital health technology solutions and unleashing information technology to win over this pandemic.

Book Synopsis Predictive and Preventive Measures for Covid-19 Pandemic by : Praveen Kumar Khosla

Download or read book Predictive and Preventive Measures for Covid-19 Pandemic written by Praveen Kumar Khosla and published by Springer Nature. This book was released on 2021-01-22 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the inputs with regard to individuals and companies who have developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, etc., that can be leveraged for strengthening the fight against coronavirus. It focuses on technology solutions to stop Covid-19 outbreak and mitigate the risk. The book contains innovative ideas from active researchers who are presently working to find solutions, and they give insights to other researchers to explore the innovative methods and predictive modeling techniques. The novel applications and techniques of established technologies like artificial intelligence (AI), Internet of things (IoT), big data, computer vision and machine learning are discussed to fight the spread of this disease, Covid-19. This pandemic has triggered an unprecedented demand for digital health technology solutions and unleashing information technology to win over this pandemic.

Data Science for COVID-19

Author: Utku Kose

Publisher: Academic Press

Published: 2021-10-22

Total Pages: 812

ISBN-13: 0323907709

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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

Book Synopsis Data Science for COVID-19 by : Utku Kose

Download or read book Data Science for COVID-19 written by Utku Kose and published by Academic Press. This book was released on 2021-10-22 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Global Healthcare Disasters

Author: Adarsh Garg

Publisher: CRC Press

Published: 2022-08-04

Total Pages: 207

ISBN-13: 1000572811

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The recent COVID-19 global pandemic exemplifies the need for efficient, reliable, and real-time tools and technology for forecasting and predicting healthcare disasters as well as for helping to restrict the subsequent spread and fatality of deadly diseases. This new book discusses many of the innovative and state-of-the-art tools and technology that can help meet the challenges of predicting such disasters. The chapters offer a plethora of useful information for designing healthcare disaster management systems that can be dynamically configurable with implementation of today’s modern technology, such as cloud computing, artificial intelligence, IoT, data analytics, and machine learning. These can increase effectiveness in remote sensing technologies, data analytics, data storage, communication networks, geographic information system (GIS), and global positioning System (GPS), to name a few. This book discusses mathematical models using graph-based approaches for analyzing dynamic, heterogeneous, and unstructured data for applications in epidemiology. The authors also address the use of mobile applications for communication efforts and remote monitoring for gauging health and the effectiveness of preventive healthcare measures. The chapters discuss influencing factors that directly or indirectly target public health infrastructure that can lead to or exacerbate global health crises, such as extreme climate changes, refugee health crises, terrorism and cyberterrorism, and technology-related incidents. The book further looks at efficient methods to analyze disasters and how to deliver healthcare in areas of conflict and crisis. This important volume, Global Healthcare Disasters: Predicting the Unpredictable with Emerging Technologies, provides a bounty of useful information for health professionals, academicians, researchers, governmental agencies, and policymakers across the world to predict, mitigate, and manage global health disaster with emerging technologies.

Book Synopsis Global Healthcare Disasters by : Adarsh Garg

Download or read book Global Healthcare Disasters written by Adarsh Garg and published by CRC Press. This book was released on 2022-08-04 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent COVID-19 global pandemic exemplifies the need for efficient, reliable, and real-time tools and technology for forecasting and predicting healthcare disasters as well as for helping to restrict the subsequent spread and fatality of deadly diseases. This new book discusses many of the innovative and state-of-the-art tools and technology that can help meet the challenges of predicting such disasters. The chapters offer a plethora of useful information for designing healthcare disaster management systems that can be dynamically configurable with implementation of today’s modern technology, such as cloud computing, artificial intelligence, IoT, data analytics, and machine learning. These can increase effectiveness in remote sensing technologies, data analytics, data storage, communication networks, geographic information system (GIS), and global positioning System (GPS), to name a few. This book discusses mathematical models using graph-based approaches for analyzing dynamic, heterogeneous, and unstructured data for applications in epidemiology. The authors also address the use of mobile applications for communication efforts and remote monitoring for gauging health and the effectiveness of preventive healthcare measures. The chapters discuss influencing factors that directly or indirectly target public health infrastructure that can lead to or exacerbate global health crises, such as extreme climate changes, refugee health crises, terrorism and cyberterrorism, and technology-related incidents. The book further looks at efficient methods to analyze disasters and how to deliver healthcare in areas of conflict and crisis. This important volume, Global Healthcare Disasters: Predicting the Unpredictable with Emerging Technologies, provides a bounty of useful information for health professionals, academicians, researchers, governmental agencies, and policymakers across the world to predict, mitigate, and manage global health disaster with emerging technologies.

Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data

Author: Siddhartha Bhattacharyya

Publisher: CRC Press

Published: 2021-11-22

Total Pages: 232

ISBN-13: 1000474704

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Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure. The book offers a comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure The accompanying case studies are based on available real-world data sets. While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.

Book Synopsis Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data by : Siddhartha Bhattacharyya

Download or read book Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data written by Siddhartha Bhattacharyya and published by CRC Press. This book was released on 2021-11-22 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Modeling, Prediction, and Diagnosis from Epidemiological Data: COVID-19 and Beyond is a handy treatise to elicit and elaborate possible intelligent mechanisms for modeling, prediction, diagnosis, and early detection of diseases arising from outbreaks of different epidemics with special reference to COVID-19. Starting with a formal introduction of the human immune systems, this book focuses on the epidemiological aspects with due cognizance to modeling, prevention, and diagnosis of epidemics. In addition, it also deals with evolving decisions on post-pandemic socio-economic structure. The book offers a comprehensive coverage of the most essential topics, including: A general overview of pandemics and their outbreak behavior A detailed overview of CI techniques Intelligent modeling, prediction, and diagnostic measures for pandemics Prognostic models Post-pandemic socio-economic structure The accompanying case studies are based on available real-world data sets. While other books may deal with this COVID-19 pandemic, none features topics covering the human immune system as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to benefit medical professionals and healthcare workers as well as the virologists who are essentially the frontline fighters of this pandemic. In addition, it also serves as a vital resource for relevant researchers in this interdisciplinary field as well as for tutors and postgraduate and undergraduate students of information sciences.

Predictive Models for Decision Support in the COVID-19 Crisis

Author: Joao Alexandre Lobo Marques

Publisher:

Published: 2021

Total Pages: 0

ISBN-13: 9783030619145

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COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

Book Synopsis Predictive Models for Decision Support in the COVID-19 Crisis by : Joao Alexandre Lobo Marques

Download or read book Predictive Models for Decision Support in the COVID-19 Crisis written by Joao Alexandre Lobo Marques and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: COVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.

Numerical Methods for Unconstrained Optimization and Nonlinear Equations

Author: J. E. Dennis, Jr.

Publisher: SIAM

Published: 1996-12-01

Total Pages: 394

ISBN-13: 9781611971200

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This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems. The algorithms covered are all based on Newton's method or "quasi-Newton" methods, and the heart of the book is the material on computational methods for multidimensional unconstrained optimization and nonlinear equation problems. The republication of this book by SIAM is driven by a continuing demand for specific and sound advice on how to solve real problems. The level of presentation is consistent throughout, with a good mix of examples and theory, making it a valuable text at both the graduate and undergraduate level. It has been praised as excellent for courses with approximately the same name as the book title and would also be useful as a supplemental text for a nonlinear programming or a numerical analysis course. Many exercises are provided to illustrate and develop the ideas in the text. A large appendix provides a mechanism for class projects and a reference for readers who want the details of the algorithms. Practitioners may use this book for self-study and reference. For complete understanding, readers should have a background in calculus and linear algebra. The book does contain background material in multivariable calculus and numerical linear algebra.

Book Synopsis Numerical Methods for Unconstrained Optimization and Nonlinear Equations by : J. E. Dennis, Jr.

Download or read book Numerical Methods for Unconstrained Optimization and Nonlinear Equations written by J. E. Dennis, Jr. and published by SIAM. This book was released on 1996-12-01 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems. The algorithms covered are all based on Newton's method or "quasi-Newton" methods, and the heart of the book is the material on computational methods for multidimensional unconstrained optimization and nonlinear equation problems. The republication of this book by SIAM is driven by a continuing demand for specific and sound advice on how to solve real problems. The level of presentation is consistent throughout, with a good mix of examples and theory, making it a valuable text at both the graduate and undergraduate level. It has been praised as excellent for courses with approximately the same name as the book title and would also be useful as a supplemental text for a nonlinear programming or a numerical analysis course. Many exercises are provided to illustrate and develop the ideas in the text. A large appendix provides a mechanism for class projects and a reference for readers who want the details of the algorithms. Practitioners may use this book for self-study and reference. For complete understanding, readers should have a background in calculus and linear algebra. The book does contain background material in multivariable calculus and numerical linear algebra.

COVID-19

Author: K. C. Santosh

Publisher:

Published: 2021

Total Pages:

ISBN-13: 9789811596834

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This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.

Book Synopsis COVID-19 by : K. C. Santosh

Download or read book COVID-19 written by K. C. Santosh and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines artificial intelligence for COVID-19 issues that are ranging from prediction to decision-making for healthcare support in human lives. Starting with major COVID-19 issues and challenges, it takes possible AI-based solutions for multiple problems, such as early prediction, its role for public health, detection of positive cases, drug analysis, and healthcare support. It mainly employs publicly available data (population) to predict who should be tested for COVID-19, for example, radiological image data to detect COVID-19 positive cases from other similar and/or different manifestations, such as pneumonia, distributed healthcare support, and supply chains in the middle of COVID-19 pandemic. The book includes recently developed AI-driven tools and techniques, such as pattern recognition, anomaly detection, machine learning, and data analytics. It covers a wide range of audience from computer science and engineering to healthcare professionals.

Intelligent Systems and Methods to Combat Covid-19

Author: Amit Joshi

Publisher: Springer Nature

Published: 2020-08-26

Total Pages: 91

ISBN-13: 9811565724

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This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.

Book Synopsis Intelligent Systems and Methods to Combat Covid-19 by : Amit Joshi

Download or read book Intelligent Systems and Methods to Combat Covid-19 written by Amit Joshi and published by Springer Nature. This book was released on 2020-08-26 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses intelligent systems and methods to prevent further spread of COVID-19, including artificial intelligence, machine learning, computer vision, signal processing, pattern recognition, and robotics. It not only explores detection/screening of COVID-19 positive cases using one type of data, such as radiological imaging data, but also examines how data analytics-based tools can help predict/project future pandemics. In addition, it highlights various challenges and opportunities, like social distancing, and addresses issues such as data collection, privacy, and security, which affect the robustness of AI-driven tools. Also investigating data-analytics-based tools for projections using time series data, pattern analysis tools for unusual pattern discovery (anomaly detection) in image data, as well as AI-enabled robotics and its possible uses, the book will appeal to a broad readership, including academics, researchers and industry professionals.

Health Informatics and Patient Safety in Times of Crisis

Author: Vajjhala, Narasimha Rao

Publisher: IGI Global

Published: 2022-12-09

Total Pages: 307

ISBN-13: 1668455005

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The COVID-19 pandemic has highlighted the importance of health data, technology, and access to health informatics. The applications of several information technologies in the context of healthcare are proving instrumental in pandemic control. These technologies were already actively used in the healthcare sector before the pandemic. However, the pandemic has resulted in researchers reassessing how these technologies could have better assisted with the aftermath of the COVID-19 pandemic and how they may mitigate the threat of future pandemics. Health Informatics and Patient Safety in Times of Crisis provides a fresh perspective on how healthcare informatics has managed the current pandemic and how improved healthcare informatics could help in a future crisis. Covering topics such as digital public health, misinformation, and knowledge management, this premier reference source is an indispensable resource for medical professionals, hospital administrators, public health officials, community leaders, international leaders, libraries, medical students, medical professors, researchers, and academicians.

Book Synopsis Health Informatics and Patient Safety in Times of Crisis by : Vajjhala, Narasimha Rao

Download or read book Health Informatics and Patient Safety in Times of Crisis written by Vajjhala, Narasimha Rao and published by IGI Global. This book was released on 2022-12-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: The COVID-19 pandemic has highlighted the importance of health data, technology, and access to health informatics. The applications of several information technologies in the context of healthcare are proving instrumental in pandemic control. These technologies were already actively used in the healthcare sector before the pandemic. However, the pandemic has resulted in researchers reassessing how these technologies could have better assisted with the aftermath of the COVID-19 pandemic and how they may mitigate the threat of future pandemics. Health Informatics and Patient Safety in Times of Crisis provides a fresh perspective on how healthcare informatics has managed the current pandemic and how improved healthcare informatics could help in a future crisis. Covering topics such as digital public health, misinformation, and knowledge management, this premier reference source is an indispensable resource for medical professionals, hospital administrators, public health officials, community leaders, international leaders, libraries, medical students, medical professors, researchers, and academicians.

Applications of Artificial Intelligence in COVID-19

Author: Sachi Nandan Mohanty

Publisher: Springer

Published: 2022-10-01

Total Pages: 0

ISBN-13: 9789811573194

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The book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, and cures, and vi) social control. It explores the use of artificial intelligence in the context of population screening and assessing infection risks, and presents mathematical models for epidemic prediction of COVID-19. Furthermore, the book discusses artificial intelligence-mediated diagnosis, and how machine learning can help in the development of drugs to treat the disease. Lastly, it analyzes various artificial intelligence-based models to improve the critical care of COVID-19 patients.

Book Synopsis Applications of Artificial Intelligence in COVID-19 by : Sachi Nandan Mohanty

Download or read book Applications of Artificial Intelligence in COVID-19 written by Sachi Nandan Mohanty and published by Springer. This book was released on 2022-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book examines the role of artificial intelligence during the COVID-19 pandemic, including its application in i) early warnings and alerts, ii) tracking and prediction, iii) data dashboards, iv) diagnosis and prognosis, v) treatments, and cures, and vi) social control. It explores the use of artificial intelligence in the context of population screening and assessing infection risks, and presents mathematical models for epidemic prediction of COVID-19. Furthermore, the book discusses artificial intelligence-mediated diagnosis, and how machine learning can help in the development of drugs to treat the disease. Lastly, it analyzes various artificial intelligence-based models to improve the critical care of COVID-19 patients.