Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Описание: In the last two decades, machine learning has been dramatically developed and is still experiencing a fast and ever-lasting change in paradigm, methodology, applications, and other aspects. This book offers a compendium of current and emerging machine learning paradigms in healthcare informatics and reflects on the diversity and complexity.
Описание: This book deepens the understanding of people through smartphone data obtained via mobile sensing and applies psychological insights for social networking applications.
Автор: Prasant Kumar Pattnaik Название: Smart Healthcare Analytics in IoT Enabled Environment ISBN: 3030375501 ISBN-13(EAN): 9783030375508 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses various aspects of how smart healthcare can be used to detect and analyze diseases, the underlying methodologies, and related security concerns.
Автор: Saxena Ankur, Brault Nicolas, Rashid Shazia Название: Big Data and Artificial Intelligence for Healthcare Applications ISBN: 036755495X ISBN-13(EAN): 9780367554958 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it. This book explores the applications in different areas of healthcare and highlights the current research.
Описание: This volume is a guide for scholars, policymakers, attorneys, teachers, judges, and students interested in the theories, policies, and doctrines of copyright law. Featuring experts from around the world, the handbook offers a systematic, comparative study of copyright in major jurisdictions including the United States, the European Union, and China.
Автор: Ritika Wason, Dinesh Goyal, Vishal Jain, S. Balamu Название: Applications of Deep Learning and Big IoT on Personalized Healthcare Services ISBN: 1799821013 ISBN-13(EAN): 9781799821014 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 37006.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Healthcare is an industry that has seen great advancements in personalized services through big data analytics. Despite the application of smart devices in the medical field, the mass volume of data that is being generated makes it challenging to correctly diagnose patients. This has led to the implementation of precise algorithms that can manage large amounts of information and successfully use smart living in medical environments. Professionals worldwide need relevant research on how to successfully implement these smart technologies within their own personalized healthcare processes.
Applications of Deep Learning and Big IoT on Personalized Healthcare Services is a pivotal reference source that provides a collection of innovative research on the analytical methods and applications of smart algorithms for the personalized treatment of patients. While highlighting topics including cognitive computing, natural language processing, and supply chain optimization, this book is ideally designed for network designers, analysts, technology specialists, medical professionals, developers, researchers, academicians, and post-graduate students seeking relevant information on smart developments within individualized healthcare.
Описание: This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud.
Описание: This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud.
Описание: The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.
Описание: This book deepens the understanding of people through smartphone data obtained via mobile sensing and applies psychological insights for social networking applications.
Автор: Tinglong Dai; Sridhar Tayur Название: Handbook of Healthcare Analytics ISBN: 1119300940 ISBN-13(EAN): 9781119300946 Издательство: Wiley Рейтинг: Цена: 17733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century?
Editors Tinglong Dai (Johns Hopkins) and Sridhar Tayur (Carnegie Mellon), aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers macro-, meso- and micro-level thrusts, spanning organizational structure, market design, access to (and quality of) care, competing interests, personalized medicine, global health, organ transplantation, healthcare supply chains, ambulatory care, inpatient care, residential care and concierge medicine. No other book in the field matches its scope. It is also the first book to synthesize what has been a highly fragmented research area--an uncoordinated accumulation of papers--and to structure it into a coherent scientific discipline. As Poincare remarked, an accumulation of facts is no more a science than a heap of stones is a house.
The handbook also provides an easy-to-comprehend introduction to five essential research tools--Markov decision process, game theory and information economics, queueing theory (with and without game theory), econometric methods, and data sciences (including machine learning)--by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.
The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook:
Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective--a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable--can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately.
Facilitates collaboration between healthcare experts and analytics scholars--to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose--ranging from queuing models imbedded with game theory ("queuing games") to game theory methods enhanced by operational considerations ("market design"), from tailored econometric methods to current day data-science methods that include algorithms from machine learning.
While the handbook is designed to be accessible to the independent reader, it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course covering the entire field.
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