Intelligent Modeling Prediction And Diagnosis From Epidemiological Data

"Intelligent Modelling, 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 out of 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 economic-social structure. The book offers 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 real-world data sets available till date. While other books may deal with this Covid-19 pandemic, none features the human immune systems as well as influences on the environmental disorder due to the ongoing pandemic. The book is primarily intended to come to the benefit of medical professionals and healthcare workers along with the virologists who are essentially the frontline fighters of Covid-19 pandemic. In addition, it would also serve as an essential resource for relevant researchers in this interdisciplinary field apart from tutors, post-graduate and under-graduate students of information sciences"--

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.

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.

This book is about building platforms for pandemic prediction. It provides an overview of probabilistic prediction for pandemic modeling based on a data-driven approach. It also provides guidance on building platforms with currently available technology using tools such as R, Shiny, and interactive plotting programs. The focus is on the integration of statistics and computing tools rather than on an in-depth analysis of all possibilities on each side. Readers can follow different reading paths through the book, depending on their needs. The book is meant as a basis for further investigation of statistical modelling, implementation tools, monitoring aspects, and software functionalities. Features: A general but parsimonious class of models to perform statistical prediction for epidemics, using a Bayesian approach Implementation of automated routines to obtain daily prediction results How to interactively visualize the model results Strategies for monitoring the performance of the predictions and identifying potential issues in the results Discusses the many decisions required to develop and publish online platforms Supplemented by an R package and its specific functionalities to model epidemic outbreaks The book is geared towards practitioners with an interest in the development and presentation of results in an online platform of statistical analysis of epidemiological data. The primary audience includes applied statisticians, biostatisticians, computer scientists, epidemiologists, and professionals interested in learning more about epidemic modelling in general, including the COVID-19 pandemic, and platform building. The authors are professors at the Statistics Department at Universidade Federal de Minas Gerais. Their research records exhibit contributions applied to a number of areas of Science, including Epidemiology. Their research activities include books published with Chapman and Hall/CRC and papers in high quality journals. They have also been involved with academic management of graduate programs in Statistics and one of them is currently the President of the Brazilian Statistical Association.

Machine learning, Internet of Things (IoT) and data analytics are new and fresh technologies that are being increasingly adopted in the field of medicine. This book positions itself at the forefront of this movement, exploring the beneficial applications of these new technologies and how they are gradually creating a smart healthcare system. This book details the various ways in which machine learning, data analytics and IoT solutions are instrumental in disease prediction in smart healthcare. For example, wearable sensors further help doctors and healthcare managers to monitor patients remotely and collect their health parameters in real-time, which can then be used to create datasets to develop machine learning models that can aid in the prediction and detection of any susceptible disease. In this way, smart healthcare can provide novel solutions to traditional medical issues. This book is a useful overview for scientists, researchers, practitioners and academics specialising in the field of intelligent healthcare, as well as containing additional appeal as a reference book for undergraduate and graduate students

The theme of this book is sustainable e-waste management through effective amalgamation of information and communication technologies (ICT) and green recycling technologies to ensure development of intelligent, smart, and sustainable systems. It encompasses multidisciplinary interventions, including recent case studies from OEMs and IT industries as well as e-waste recyclers, and explores interdisciplinary research and industry–academia collaborations towards the development of smart and sustainable systems for e-waste management. Features: Covers the application of smart and intelligent systems for e-waste management. Explores recent advancements from the technological aspect – both recycling and ICT. Reviews supply chain criticalities for e-waste. Aims at cleaner production and intelligent systems for a green digital economy. Includes real-life case studies reflecting industry standards and the current paradigm. This book is aimed at graduate students and researchers in environmental engineering, waste management, urban mining, circular economy, waste processing, electronics and telecommunication engineering, electrical and electronics engineering, and chemical engineering.

Digital India: Navigating Sustainable Development Goals is a comprehensive edited volume exploring India's transformative digital journey in alignment with the Sustainable Development Goals (SDGs). This resource-rich book caters to academics, researchers, policymakers, practitioners, students and global stakeholders. Covering diverse topics such as the impact of COVID-19 on education, Fintech adoption, gender justice, and sustainability challenges, it provides a nuanced understanding of the intersection between technology and sustainable development. The book serves as a valuable resource for gaining insights into the practical implications of Digital India initiatives and their role in achieving SDGs.

Supply chain management, often known as SCM, refers to the extensive variety of operations that are required to plan, monitor, and coordinate the movement of a product from its raw materials to its finished state in the most time- and money-efficient manner possible. How the supply chain is managed has an impact not only on the quality of the product and the service but also on the distribution, costs, and overall customer experience. Supply chain management is a massive undertaking that needs firms to reevaluate the method in which they operate their supply chains. Blockchain, IoT, and AI Technologies for Supply Chain Management discusses the problems and difficulties that the facilitators of the supply chain confront, in addition to the possible solutions to such problems and difficulties. This book will be the only one of its kind to address the impact of COVID-19 on supply chain systems involving different stakeholders such as producers, dealers, and manufacturers and will provide a foundation for future research opportunities that will allow for the unrestricted expansion and prosperity of business. It will serve as a foundation for academics, scientists, and educationists interested in the use of modern technologies in the field of supply chain management, such as the Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain. In addition to those engaged in research, undergraduate and postgraduate students in higher education can also use this publication as a reference book. This book also presents a multifaceted perspective for the general public, including topics such as computer science, the food business, hotel management, fashion, medical, inventory management, and agricultural spheres.