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Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management
  • Author : Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
  • Publisher :Unknown
  • Release Date :2019-04-15
  • Total pages :312
  • ISBN : 9780128181478
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Summary : Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Healthcare Data Analytics and Management

Healthcare Data Analytics and Management
  • Author : Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
  • Publisher :Unknown
  • Release Date :2018-11-15
  • Total pages :340
  • ISBN : 9780128156360
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Summary : 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

Next Generation Technology Driven Precission Medicine and Smart Healthcare

Next Generation Technology Driven Precission Medicine and Smart Healthcare
  • Author : Miltiadis D. Lytras,Anna Visvizi,Akila Sarirete
  • Publisher :Unknown
  • Release Date :2020-09-01
  • Total pages :380
  • ISBN : 9780128220627
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Summary : Next Generation Technology Driven Precission Medicine and Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers

Big Data Analytics and Intelligence

Big Data Analytics and Intelligence
  • Author : Poonam Tanwar,Vishal Jain,Chuan-Ming Liu,Vishal Goyal
  • Publisher :Unknown
  • Release Date :2020-09-30
  • Total pages :392
  • ISBN : 9781839091018
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Summary : 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.

Big Data and Health Analytics

Big Data and Health Analytics
  • Author : Katherine Marconi,Harold Lehmann
  • Publisher :Unknown
  • Release Date :2014-12-20
  • Total pages :382
  • ISBN : 9781482229257
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Summary : Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery.Written for healt

Big Data Analytics in Healthcare

Big Data Analytics in Healthcare
  • Author : Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki
  • Publisher :Unknown
  • Release Date :2019-10-01
  • Total pages :187
  • ISBN : 9783030316723
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Summary : This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach

Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
  • Author : Aboul-Ella Hassanien,Nilanjan Dey,Sally Elghamrawy
  • Publisher :Unknown
  • Release Date :2020-11-13
  • Total pages :307
  • ISBN : 9783030552589
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Summary : 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.

Data Science for Healthcare

Data Science for Healthcare
  • Author : Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
  • Publisher :Unknown
  • Release Date :2019-02-23
  • Total pages :367
  • ISBN : 9783030052492
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Summary : 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.

IoT-Based Data Analytics for the Healthcare Industry

IoT-Based Data Analytics for the Healthcare Industry
  • Author : Sanjay Kumar Singh,Ravi Shankar Singh,Anil Kumar Pandey,Sandeep S Udmale,Ankit Chaudhary
  • Publisher :Unknown
  • Release Date :2020-12-01
  • Total pages :340
  • ISBN : 9780128214763
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Summary : 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

Machine Learning for Intelligent Decision Science

Machine Learning for Intelligent Decision Science
  • Author : Jitendra Kumar Rout
  • Publisher :Unknown
  • Release Date :2021
  • Total pages :229
  • ISBN : 9789811536892
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Summary :

Managerial Perspectives on Intelligent Big Data Analytics

Managerial Perspectives on Intelligent Big Data Analytics
  • Author : Sun, Zhaohao
  • Publisher :Unknown
  • Release Date :2019-02-22
  • Total pages :335
  • ISBN : 9781522572787
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Summary : 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.

Demystifying Big Data and Machine Learning for Healthcare

Demystifying Big Data and Machine Learning for Healthcare
  • Author : Prashant Natarajan,John C. Frenzel,Detlev H. Smaltz
  • Publisher :Unknown
  • Release Date :2017-02-15
  • Total pages :210
  • ISBN : 9781315389301
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Summary : Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Intelligent Systems for Healthcare Management and Delivery

Intelligent Systems for Healthcare Management and Delivery
  • Author : Bouchemal, Nardjes
  • Publisher :Unknown
  • Release Date :2018-12-07
  • Total pages :377
  • ISBN : 9781522570721
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Summary : With the growing use of new technologies and artificial intelligence (AI) applications, intelligent systems can be used to manage large amounts of existing data in healthcare domains. Having more intelligent methods for accessing data allows medical professionals to more efficiently identify the best medical practices and more concrete solutions for diagnosing and treating a multitude of rare diseases. Intelligent Systems for Healthcare Management and Delivery provides relevant and advanced methodological, technological, and scientific approaches related to the application of sophisticated exploitation of AI, as well as providing insight into the technologies and intelligent applications that have received growing attention in recent years such as medical imaging, EMR systems, and drug development assistance. This publication fosters a scientific debate for new healthcare intelligent systems and sophisticated approaches for enhanced healthcare services and is ideally designed for medical professionals, hospital staff, rehabilitation specialists, medical educators, and researchers.

Applications of Big Data in Healthcare

Applications of Big Data in Healthcare
  • Author : Ashish Khanna,Deepak Gupta,Nilanjan Dey
  • Publisher :Unknown
  • Release Date :2021-02-01
  • Total pages :332
  • ISBN : 9780128204511
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Summary : Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big Data and suggests ways to overcome them, with a primary emphasis on data repositories, challenges, and concepts for data scientists, engineers and clinicians. The applications of Big Data have grown tremendously within the past few years and its growth can not only be attributed to its competence to handle large data streams but also to its abilities to find insights from complex, noisy, heterogeneous, longitudinal and voluminous data. The main objectives of Big Data in the healthcare sector is to come up with ways to provide personalized healthcare to patients by taking into account the enormous amounts of already existing data. Provides case studies that illustrate the business processes underlying the use of big data and deep learning health analytics to improve health care delivery Supplies readers with a foundation for further specialized study in clinical analysis and data management Includes links to websites, videos, articles and other online content to expand and support the primary learning objectives for each major section of the book

Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications

Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications
  • Author : Management Association, Information Resources
  • Publisher :Unknown
  • Release Date :2019-12-06
  • Total pages :2071
  • ISBN : 9781799812050
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Summary : Advancements in data science have created opportunities to sort, manage, and analyze large amounts of data more effectively and efficiently. Applying these new technologies to the healthcare industry, which has vast quantities of patient and medical data and is increasingly becoming more data-reliant, is crucial for refining medical practices and patient care. Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications is a vital reference source that examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations. Highlighting a range of topics such as data security and privacy, health informatics, and predictive analytics, this multi-volume book is ideally designed for doctors, hospital administrators, nurses, medical professionals, IT specialists, computer engineers, information technologists, biomedical engineers, data-processing specialists, healthcare practitioners, academicians, and researchers interested in current research on the connections between data analytics in the field of medicine.

Handbook of Data Science Approaches for Biomedical Engineering

Handbook of Data Science Approaches for Biomedical Engineering
  • Author : Valentina E. Balas,Vijender Kumar Solanki,Raghvendra Kumar,Manju Khari
  • Publisher :Unknown
  • Release Date :2019-11-13
  • Total pages :318
  • ISBN : 9780128183199
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Summary : Handbook of Data Science Approaches for Biomedical Engineering covers the research issues and concepts of biomedical engineering progress and the ways they are aligning with the latest technologies in IoT and big data. In addition, the book includes various real-time/offline medical applications that directly or indirectly rely on medical and information technology. Case studies in the field of medical science, i.e., biomedical engineering, computer science, information security, and interdisciplinary tools, along with modern tools and the technologies used are also included to enhance understanding. Today, the role of Big Data and IoT proves that ninety percent of data currently available has been generated in the last couple of years, with rapid increases happening every day. The reason for this growth is increasing in communication through electronic devices, sensors, web logs, global positioning system (GPS) data, mobile data, IoT, etc. Provides in-depth information about Biomedical Engineering with Big Data and Internet of Things Includes technical approaches for solving real-time healthcare problems and practical solutions through case studies in Big Data and Internet of Things Discusses big data applications for healthcare management, such as predictive analytics and forecasting, big data integration for medical data, algorithms and techniques to speed up the analysis of big medical data, and more

Healthcare and Big Data Management

Healthcare and Big Data Management
  • Author : Bairong Shen
  • Publisher :Unknown
  • Release Date :2017-10-20
  • Total pages :164
  • ISBN : 9789811060410
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Summary : The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare; physiological and gut microbiota – data collection and analysis; big data standardization and ontology; and personal data privacy and systems level modeling in the healthcare context. The book offers a valuable resource for biomedical informaticians, clinicians, health practitioners and researchers alike.

Analytics in Healthcare

Analytics in Healthcare
  • Author : Christo El Morr,Hossam Ali-Hassan
  • Publisher :Unknown
  • Release Date :2019-01-21
  • Total pages :105
  • ISBN : 9783030045067
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Summary : This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
  • Author : Adam Bohr,Kaveh Memarzadeh
  • Publisher :Unknown
  • Release Date :2020-06-21
  • Total pages :378
  • ISBN : 9780128184394
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Summary : Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Early Detection of Neurological Disorders Using Machine Learning Systems

Early Detection of Neurological Disorders Using Machine Learning Systems
  • Author : Paul, Sudip,Bhattacharya, Pallab,Bit, Arindam
  • Publisher :Unknown
  • Release Date :2019-06-28
  • Total pages :376
  • ISBN : 9781522585688
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Summary : While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications
  • Author : Arun Kumar Sangaiah,Zhiyong Zhang,Michael Sheng
  • Publisher :Unknown
  • Release Date :2018-08-21
  • Total pages :362
  • ISBN : 9780128133279
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Summary : Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering. It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful. Presents a brief overview of computational intelligence paradigms and its significant role in application domains Illustrates the state-of-the-art and recent developments in the new theories and applications of CI approaches Familiarizes the reader with computational intelligence concepts and technologies that are successfully used in the implementation of cloud-centric multimedia services in massive data processing Provides new advances in the fields of CI for bio-engineering application