Data Science for Effective Healthcare Systems
Data Science for Effective Healthcare Systems

Author: Hari Singh

Publisher: CRC Press

Published: 2022-07-27

Total Pages: 275

ISBN-13: 1000618854

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Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing, detection & prevention from COVID-19 virus, drug discovery, early prediction, and prevention of diseases are some thrust areas where data science has proven to be indispensable. Key Features: The book offers comprehensive coverage of the most essential topics, including: Big Data Analytics, Applications & Challenges in Healthcare Descriptive, Predictive and Prescriptive Analytics in Healthcare Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, Brain Tumor The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least, this book will surely benefit research scholar, persons associated with healthcare, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.

Data Science for Healthcare
Data Science for Healthcare

Author: Sergio Consoli

Publisher: Springer

Published: 2019-03-22

Total Pages: 367

ISBN-13: 9783030052485

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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.

Strategic Data Management for Successful Healthcare Outcomes
Strategic Data Management for Successful Healthcare Outcomes

Author: Hema Lakkaraju

Publisher:

Published: 2021-11-30

Total Pages: 106

ISBN-13: 9781637421499

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The healthcare landscape continues to evolve in an effort to accommodate our ever-connected world. A digital healthcare system poses new challenges and exposes existing issues as professionals--like you--strive to solve concerns. This book recognizes the unique tasks of dedicated professionals while attempting to decrease confusion on this key topic. It's time to discuss why strategy is important for modern healthcare data management, how strategy can create new business or upscale a business in healthcare data management, and how these tactics assist your business in gaining a competitive advantage. Cut through the frustration generated by the staggering amount of healthcare data currently being created, collected, and distributed--this book will teach you how. This book will help you to understand: Critical types of data How to strategically manage data How to build better patient care Tips for improving performance New ways for your business to thrive.

Healthcare Data Analytics
Healthcare Data Analytics

Author: Chandan K. Reddy

Publisher: CRC Press

Published: 2020-06-30

Total Pages: 760

ISBN-13: 9780367575687

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Supplying a comprehensive overview of healthcare analytics research, Healthcare Data Analytics provides an understanding of the analytical techniques currently available to solve healthcare problems. The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent devel

Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Handbook of Research on Data Science for Effective Healthcare Practice and Administration

Author: Noughabi, Elham Akhond Zadeh

Publisher: IGI Global

Published: 2017-07-20

Total Pages: 574

ISBN-13: 1522525165

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Data science has always been an effective way of extracting knowledge and insights from information in various forms. One industry that can utilize the benefits from the advances in data science is the healthcare field. The Handbook of Research on Data Science for Effective Healthcare Practice and Administration is a critical reference source that overviews the state of data analysis as it relates to current practices in the health sciences field. Covering innovative topics such as linear programming, simulation modeling, network theory, and predictive analytics, this publication is recommended for all healthcare professionals, graduate students, engineers, and researchers that are seeking to expand their knowledge of efficient techniques for information analysis in the healthcare professions.

Semantic Web for Effective Healthcare Systems
Semantic Web for Effective Healthcare Systems

Author: Vishal Jain

Publisher: John Wiley & Sons

Published: 2021-12-09

Total Pages: 356

ISBN-13: 1119762294

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SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMS The book summarizes the trends and current research advances in web semantics, delineating the existing tools, techniques, methodologies, and research solutions Semantic Web technologies have the opportunity to transform the way healthcare providers utilize technology to gain insights and knowledge from their data and make treatment decisions. Both Big Data and Semantic Web technologies can complement each other to address the challenges and add intelligence to healthcare management systems. The aim of this book is to analyze the current status on how the semantic web is used to solve health data integration and interoperability problems, and how it provides advanced data linking capabilities that can improve search and retrieval of medical data. Chapters analyze the tools and approaches to semantic health data analysis and knowledge discovery. The book discusses the role of semantic technologies in extracting and transforming healthcare data before storing it in repositories. It also discusses different approaches for integrating heterogeneous healthcare data. This innovative book offers: The first of its kind and highlights only the ontology driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems; Presents a comprehensive examination of the emerging research in areas of the semantic web; Discusses studies on new research areas including ontological engineering, semantic annotation and semantic sentiment analysis; Helps readers understand key concepts in semantic web applications for the biomedical engineering and healthcare fields; Includes coverage of key application areas of the semantic web. Audience: Researchers and graduate students in computer science, biomedical engineering, electronic and software engineering, as well as industry scientific researchers, clinicians, and systems managers in biomedical fields.

Exploratory Data Analytics for Healthcare
Exploratory Data Analytics for Healthcare

Author: R. Lakshmana Kumar

Publisher: CRC Press

Published: 2021-12-23

Total Pages: 307

ISBN-13: 1000527018

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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.

Big Data and Health Analytics
Big Data and Health Analytics

Author: Katherine Marconi

Publisher: CRC Press

Published: 2014-12-20

Total Pages: 374

ISBN-13: 1482229250

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This book 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 health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery.

Healthcare Data Analytics and Management
Healthcare Data Analytics and Management

Author: Nilanjan Dey

Publisher: Academic Press

Published: 2018-11-15

Total Pages: 342

ISBN-13: 0128156368

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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

Machine Learning and Analytics in Healthcare Systems
Machine Learning and Analytics in Healthcare Systems

Author: Himani Bansal

Publisher: CRC Press

Published: 2021-06-30

Total Pages: 275

ISBN-13: 1000406199

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This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine. It will combine the design and problem-solving skills of engineering with health sciences, in order to advance healthcare treatment. The book will include areas such as diagnosis, monitoring, and therapy. The book will provide real-world case studies, gives a detailed exploration of applications in healthcare systems, offers multiple perspectives on a variety of disciplines, while also letting the reader know how to avoid some of the consequences of old methods with data sharing. The book can be used as a reference for practitioners, researchers and for students at basic and intermediary levels in Computer Science, Electronics and Communications.