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Handbook of Research on Foundations and Applications of Intelligent Business Analytics
Language: en
Pages: 425
Authors: Sun, Zhaohao, Wu, Zhiyou
Categories: Computers
Type: BOOK - Published: 2022-03-11 - Publisher: IGI Global

Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
The Science of Health Disparities Research
Language: en
Pages: 528
Authors: Irene Dankwa-Mullan, Eliseo J. Pérez-Stable, Kevin L. Gardner, Xinzhi Zhang, Adelaida M. Rosario
Categories: Science
Type: BOOK - Published: 2021-03-01 - Publisher: John Wiley & Sons

Integrates the various disciplines of the science of health disparities in one comprehensive volume The Science of Health Disparities Research is an indispensable source of up-to-date information on clinical and translational health disparities science. Building upon the advances in health disparities research over the past decade, this authoritative volume informs policies and practices addressing the diseases, disorders, and gaps in health outcomes that are more prevalent in minority populations and socially disadvantaged communities. Contributions by recognized scholars and leaders in the field—featuring contemporary research, conceptual models, and a broad range of scientific perspectives—provide an interdisciplinary approach to reducing inequalities in population health, encouraging community engagement in the research process, and promoting social justice. In-depth chapters help readers better understand the specifics of minority health and health disparities while demonstrating the importance of advancing theory, refining measurement, improving investigative methods, and diversifying scientific research. In 26 chapters, the book examines topics including the etiology of health disparities research, the determinants of population health, research ethics, and research in African American, Asians, Latino, American Indian, and other vulnerable populations. Providing a unified framework on the principles and applications of the science of health disparities research, this important volume: Defines the field of health disparities science and suggests new directions in scholarship and research Explains basic definitions, principles, and concepts for identifying, understanding and addressing health disparities Provides guidance on both conducting health disparities research and translating the results Examines how social, historical and contemporary injustices may influence the health of racial and ethnic minorities Illustrates the increasing national and global importance of addressing health disparities Discusses population health training, capacity-building, and the transdisciplinary tools needed to advance health equity A significant contribution to the field, The Science of Health Disparities Research is an essential resource for students and basic and clinical researchers in genetics, population genetics, and public health, health care policymakers, and epidemiologists, medical students, and clinicians, particularly those working with minority, vulnerable, or underserved populations.
Big Data Analytics Methods
Language: en
Pages: 254
Authors: Peter Ghavami
Categories: Business & Economics
Type: BOOK - Published: 2019-12-16 - Publisher: Walter de Gruyter GmbH & Co KG

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.
Advances on Broad-Band Wireless Computing, Communication and Applications
Language: en
Pages: 464
Authors: Leonard Barolli, Makoto Takizawa, Tomoya Enokido, Hsing-Chung Chen, Keita Matsuo
Categories: Technology & Engineering
Type: BOOK - Published: 2020-10-07 - Publisher: Springer Nature

This book aims to provide the latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of broadband and wireless computing. Information networks of today are going through a rapid evolution. Different kinds of networks with different characteristics are emerging, and they are integrating in heterogeneous networks. For these reasons, there are many interconnection problems which may occur at different levels of the hardware and software design of communicating entities and communication networks. These kinds of networks need to manage an increasing usage demand, provide support for a significant number of services, guarantee their QoS, and optimize the network resources. The success of all-IP networking and wireless technology has changed the ways of living the people around the world. The progress of electronic integration and wireless communications is going to pave the way to offer people the access to the wireless networks on the fly, based on which all electronic devices will be able to exchange the information with each other in ubiquitous way whenever necessary.
Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
Language: en
Pages: 307
Authors: Aboul-Ella Hassanien, Nilanjan Dey, Sally Elghamrawy
Categories: Computers
Type: BOOK - Published: 2020-10-12 - Publisher: Springer Nature

This book includes research articles and expository papers on the applications of artificial intelligence and big data analytics to battle the pandemic. In the context of COVID-19, this book focuses on how big data analytic and artificial intelligence help fight COVID-19. The book is divided into four parts. The first part discusses the forecasting and visualization of the COVID-19 data. The second part describes applications of artificial intelligence in the COVID-19 diagnosis of chest X-Ray imaging. The third part discusses the insights of artificial intelligence to stop spread of COVID-19, while the last part presents deep learning and big data analytics which help fight the COVID-19.
Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics
Language: en
Pages: 352
Authors: Sunil Kumar Dhal, Srinivas Prasad, Sudhir Kumar Mohapatra, Subhendu Kumar Pani
Categories: Computers
Type: BOOK - Published: 2022-05-20 - Publisher: John Wiley & Sons

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.
The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume I
Language: en
Pages: 328
Authors: Sezer Bozkuş Kahyaoğlu
Categories: Business & Economics
Type: BOOK - Published: 2021-04-26 - Publisher: Springer Nature

The book discusses the effects of artificial intelligence in terms of economics and finance. In particular, the book focuses on the effects of the change in the structure of financial markets, institutions and central banks, along with digitalization analyzed based on fintech ecosystems. In addition to finance sectors, other sectors, such as health, logistics, and industry 4.0, all of which are undergoing an artificial intelligence induced rapid transformation, are addressed in this book. Readers will receive an understanding of an integrated approach towards the use of artificial intelligence across various industries and disciplines with a vision to address the strategic issues and priorities in the dynamic business environment in order to facilitate decision-making processes. Economists, board members of central banks, bankers, financial analysts, regulatory authorities, accounting and finance professionals, chief executive officers, chief audit officers and chief financial officers, chief financial officers, as well as business and management academic researchers, will benefit from reading this book.
Big Data and Learning Analytics in Higher Education
Language: en
Pages: 272
Authors: Ben Kei Daniel
Categories: Education
Type: BOOK - Published: 2016-08-27 - Publisher: Springer

​This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​.
Artificial Intelligence Research and Development
Language: en
Pages: 420
Authors: Z. Falomir, K. Gibert, E. Plaza
Categories: Computers
Type: BOOK - Published: 2018-10-04 - Publisher: IOS Press

It is almost impossible today to find an economic sector or aspect of society which does not involve AI techniques in some way. This pervasive technology has become indispensible in a multitude of ways, from supporting decision making to managing digital devices such as smart sensors, mechanical arms or artificial eyes. The ability of AI to emulate intelligence in the resolution of challenging problems has placed it at the centre of problem solving in all areas of our society. This book presents contributions from CCIA 2018, the 21st International Conference of the Catalan Association for Artificial Intelligence which took place in Alt Empordà, Catalonia, Spain, on 8-10th October 2018. The book aims to provide a picture of what is being achieved and what is under development in AI today. As such, its contents represent the diversity of approaches and applications currently being researched, but it also presents invited contributions which deal with some of the challenges that will have to be faced in the decade to come. The contributions included in this book are organized under the following headings: logic, satisfiability and fuzzy sets; classifiers, networks and machine learning; data science, recommender systems and case-based reasoning; natural language and sound processing; cognitive systems and agents; and computer vision and robotics. The book also covers a number of current AI challenges and new trends like big data, spatial problem solving, ethics and AI, and how blockchain impacts AI. Providing an up-to-the-minute overview of current AI technology and research, this book will be of value to all those with an interest in the subject.
Managerial Perspectives on Intelligent Big Data Analytics
Language: en
Pages: 335
Authors: Sun, Zhaohao
Categories: Computers
Type: BOOK - Published: 2019-02-22 - Publisher: IGI Global

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.
Fintech with Artificial Intelligence, Big Data, and Blockchain
Language: en
Pages: 304
Authors: Paul Moon Sub Choi, Seth H. Huang
Categories: Technology & Engineering
Type: BOOK - Published: 2021-03-08 - Publisher: Springer Nature

This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.
Data Analytics, Computational Statistics, and Operations Research for Engineers
Language: en
Pages: 296
Authors: Debabrata Samanta, SK Hafizul Islam, Naveen Chilamkurti, Mohammad Hammoudeh
Categories: Technology & Engineering
Type: BOOK - Published: 2022-04-05 - Publisher: CRC Press

With the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.