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Author: Philippe J. Giabbanelli Publisher: Springer ISBN: 3319779117 Category : Technology & Engineering Languages : en Pages : 221
Book Description
This book introduces readers to the methods, types of data, and scale of analysis used in the context of health. The challenges of working with big data are explored throughout the book, while the benefits are also emphasized through the discoveries made possible by linking large datasets. Methods include thorough case studies from statistics, as well as the newest facets of data analytics: data visualization, modeling and simulation, and machine learning. The diversity of datasets is illustrated through chapters on networked data, image processing, and text, in addition to typical structured numerical datasets. While the methods, types of data, and scale have been individually covered elsewhere, by bringing them all together under one “umbrella” the book highlights synergies, while also helping scholars fluidly switch between tools as needed. New challenges and emerging frontiers are also discussed, helping scholars grasp how methods will need to change in response to the latest challenges in health.
Author: Chandan K. Reddy Publisher: CRC Press ISBN: 148223212X Category : Business & Economics Languages : en Pages : 756
Book Description
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available
Author: Sanjay Kumar Singh Publisher: Academic Press ISBN: 0128214767 Category : Technology & Engineering Languages : en Pages : 342
Book Description
IoT Based Data Analytics for the Healthcare Industry: Techniques and Applications explores recent advances in the analysis of healthcare industry data through IoT data analytics. The book covers the analysis of ubiquitous data generated by the healthcare industry, from a wide range of sources, including patients, doctors, hospitals, and health insurance companies. The book provides AI solutions and support for healthcare industry end-users who need to analyze and manipulate this vast amount of data. These solutions feature deep learning and a wide range of intelligent methods, including simulated annealing, tabu search, genetic algorithm, ant colony optimization, and particle swarm optimization. The book also explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages, challenges and issues in data collection, data handling, and data collection set-up. Healthcare industry data or streaming data generated by ubiquitous sensors cocooned into the IoT requires advanced analytics to transform data into information. With advances in computing power, communications, and techniques for data acquisition, the need for advanced data analytics is in high demand. - Provides state-of-art methods and current trends in data analytics for the healthcare industry - Addresses the top concerns in the healthcare industry using IoT and data analytics, and machine learning and deep learning techniques - Discusses several potential AI techniques developed using IoT for the healthcare industry - Explores challenges, opportunities, and future research directions, and discusses the data collection and pre-processing stages
Author: Sergio Consoli Publisher: Springer ISBN: 3030052494 Category : Computers Languages : en Pages : 367
Book Description
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.
Author: Poonam Tanwar Publisher: Emerald Group Publishing ISBN: 1839090995 Category : Business & Economics Languages : en Pages : 392
Book Description
Big Data Analytics and Intelligence is essential reading for researchers and experts working in the fields of health care, data science, analytics, the internet of things, and information retrieval.
Author: Nilanjan Dey Publisher: Academic Press ISBN: 0128156368 Category : Science Languages : en Pages : 342
Book Description
Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. - Covers data analysis, management and security concepts and tools in the healthcare domain - Highlights electronic medical health records and patient information records - Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining - Includes multidisciplinary contributions in relation to healthcare applications and challenges
Author: Philippe J. Giabbanelli Publisher: Springer ISBN: 3319779117 Category : Technology & Engineering Languages : en Pages : 221
Book Description
This book introduces readers to the methods, types of data, and scale of analysis used in the context of health. The challenges of working with big data are explored throughout the book, while the benefits are also emphasized through the discoveries made possible by linking large datasets. Methods include thorough case studies from statistics, as well as the newest facets of data analytics: data visualization, modeling and simulation, and machine learning. The diversity of datasets is illustrated through chapters on networked data, image processing, and text, in addition to typical structured numerical datasets. While the methods, types of data, and scale have been individually covered elsewhere, by bringing them all together under one “umbrella” the book highlights synergies, while also helping scholars fluidly switch between tools as needed. New challenges and emerging frontiers are also discussed, helping scholars grasp how methods will need to change in response to the latest challenges in health.
Author: Jesus Rogel-Salazar Publisher: CRC Press ISBN: 0429822324 Category : Business & Economics Languages : en Pages : 424
Book Description
Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. Features: Targets readers with a background in programming, who are interested in the tools used in data analytics and data science Uses Python throughout Presents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs Focuses on the practical use of the tools rather than on lengthy explanations Provides the reader with the opportunity to use the book whenever needed rather than following a sequential path The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences – in this case, literally to the users’ fingertips in the form of an iPhone app. About the Author Dr. Jesús Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.
Author: R. Lakshmana Kumar Publisher: CRC Press ISBN: 1000527018 Category : Computers Languages : en Pages : 307
Book Description
Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way. The book addresses the complete data visualization technologies workflow, explores basic and high-level concepts of computer science and engineering in medical science, and provides an overview of the clinical scientific research areas that enables smart diagnosis equipment. It will discuss techniques and tools used to explore large volumes of medical data and offers case studies that focus on the innovative technological upgradation and challenges faced today. The primary audience for the book includes specialists, researchers, graduates, designers, experts, physicians, and engineers who are doing research in this domain.
Author: Ewen Harrison Publisher: CRC Press ISBN: 1000226166 Category : Medical Languages : en Pages : 354
Book Description
In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.
Author: Connie White Delaney Publisher: CRC Press ISBN: 1000573389 Category : Medical Languages : en Pages : 155
Book Description
In just the past decade, the emergence of digital health has finally become palpable. Enhanced by the pandemic, social justice events, and planetary health urgency, Realizing Digital Health – Bold Challenges and Opportunities for Nursing explores that evolution with a focus on capturing the current state of digital health. Anchored in an introduction to digital health, new technologies, opportunities, and challenges are described. Consideration of the opportunities and challenges of digital health calls for specific attention to ethical considerations. This book includes a current state synopsis of healthcare in the USA, with the inclusion of specific implications for nursing leaders and executives. Engagement of the people (patients, families, communities) working in partnership to enhance health is described. Information management and the necessary definition and access to data are discussed with a particular explication of the function of information management and operational decision-making. The challenges and learnings related to informatics drawn from the experiences of leaders in large health systems shed insight into the current state of informatics-enabled digital health and healthcare. The global example of the integration of technology, nursing, and health systems expands our knowledge of the current state as well as explores possibilities. This book concludes with a commitment to and description of the current state of teamwork and the integral role/functions within informatics, nursing, and healthcare. This book provides the reader with a succinct overview of digital technologies, a reality-anchored description of the current state in the USA and globally and highlights the core foundation and integration of informatics and information management. This book stimulates thought and actions to advance digital health within a full partnership among the people, organizations, systems, and global imperatives including planetary survival. This book lifts up the next era calling for full teamwork, collaboration, and partnership as we emerge into a true global community. Nursing and Informatics for the 21st Century – Embracing a Digital World, 3rd Edition is comprised of four books which can be purchased individually: Book 1: Realizing Digital Health – Bold Challenges and Opportunities for Nursing Book 2: Nursing Education and Digital Health Strategies Book 3: Innovation, Technology, and Applied Informatics for Nurses Book 4: Nursing in an Integrated Digital World that Supports People, Systems, and the Planet
Author: Philippe J. Giabbanelli
Author: Chandan K. Reddy
Author: Sanjay Kumar Singh
Author: Sergio Consoli
Author: Poonam Tanwar
Author: Nilanjan Dey
Author: Philippe J. Giabbanelli
Author: Jesus Rogel-Salazar
Author: R. Lakshmana Kumar
Author: Ewen Harrison
Author: Connie White Delaney