Data Science For Healthcare

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R for Health Data Science

Author : Ewen Harrison,Riinu Pius
Publisher : CRC Press
Page : 354 pages
File Size : 53,6 Mb
Release : 2020-12-31
Category : Medical
ISBN : 9781000226164

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R for Health Data Science by Ewen Harrison,Riinu Pius Pdf

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.

Data Science for Healthcare

Author : Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
Publisher : Springer
Page : 367 pages
File Size : 53,7 Mb
Release : 2019-02-23
Category : Computers
ISBN : 9783030052492

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Data Science for Healthcare by Sergio Consoli,Diego Reforgiato Recupero,Milan Petković Pdf

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.

Data Science for Effective Healthcare Systems

Author : Hari Singh,Ravindara Bhatt,Prateek Thakral,Dinesh Chander Verma
Publisher : CRC Press
Page : 275 pages
File Size : 55,5 Mb
Release : 2022-07-27
Category : Computers
ISBN : 9781000618853

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Data Science for Effective Healthcare Systems by Hari Singh,Ravindara Bhatt,Prateek Thakral,Dinesh Chander Verma Pdf

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.

Leveraging Data Science for Global Health

Author : Leo Anthony Celi,Maimuna S. Majumder,Patricia Ordóñez,Juan Sebastian Osorio,Kenneth E. Paik,Melek Somai
Publisher : Springer Nature
Page : 471 pages
File Size : 40,7 Mb
Release : 2020-07-31
Category : Medical
ISBN : 9783030479947

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Leveraging Data Science for Global Health by Leo Anthony Celi,Maimuna S. Majumder,Patricia Ordóñez,Juan Sebastian Osorio,Kenneth E. Paik,Melek Somai Pdf

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.

Healthcare Data Analytics

Author : Chandan K. Reddy,Charu C. Aggarwal
Publisher : CRC Press
Page : 756 pages
File Size : 43,6 Mb
Release : 2015-06-23
Category : Business & Economics
ISBN : 9781482232127

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Healthcare Data Analytics by Chandan K. Reddy,Charu C. Aggarwal Pdf

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

Fundamentals of Clinical Data Science

Author : Pieter Kubben,Michel Dumontier,Andre Dekker
Publisher : Springer
Page : 219 pages
File Size : 40,7 Mb
Release : 2018-12-21
Category : Medical
ISBN : 9783319997131

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Fundamentals of Clinical Data Science by Pieter Kubben,Michel Dumontier,Andre Dekker Pdf

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Statistics for Health Data Science

Author : Ruth Etzioni,Micha Mandel,Roman Gulati
Publisher : Springer Nature
Page : 238 pages
File Size : 51,6 Mb
Release : 2021-01-04
Category : Medical
ISBN : 9783030598891

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Statistics for Health Data Science by Ruth Etzioni,Micha Mandel,Roman Gulati Pdf

Students and researchers in the health sciences are faced with greater opportunity and challenge than ever before. The opportunity stems from the explosion in publicly available data that simultaneously informs and inspires new avenues of investigation. The challenge is that the analytic tools required go far beyond the standard methods and models of basic statistics. This textbook aims to equip health care researchers with the most important elements of a modern health analytics toolkit, drawing from the fields of statistics, health econometrics, and data science. This textbook is designed to overcome students’ anxiety about data and statistics and to help them to become confident users of appropriate analytic methods for health care research studies. Methods are presented organically, with new material building naturally on what has come before. Each technique is motivated by a topical research question, explained in non-technical terms, and accompanied by engaging explanations and examples. In this way, the authors cultivate a deep (“organic”) understanding of a range of analytic techniques, their assumptions and data requirements, and their advantages and limitations. They illustrate all lessons via analyses of real data from a variety of publicly available databases, addressing relevant research questions and comparing findings to those of published studies. Ultimately, this textbook is designed to cultivate health services researchers that are thoughtful and well informed about health data science, rather than data analysts. This textbook differs from the competition in its unique blend of methods and its determination to ensure that readers gain an understanding of how, when, and why to apply them. It provides the public health researcher with a way to think analytically about scientific questions, and it offers well-founded guidance for pairing data with methods for valid analysis. Readers should feel emboldened to tackle analysis of real public datasets using traditional statistical models, health econometrics methods, and even predictive algorithms. Accompanying code and data sets are provided in an author site: https://roman-gulati.github.io/statistics-for-health-data-science/

Healthcare Data Analytics and Management

Author : Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt
Publisher : Academic Press
Page : 340 pages
File Size : 43,9 Mb
Release : 2018-11-15
Category : Science
ISBN : 9780128156360

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Healthcare Data Analytics and Management by Nilanjan Dey,Amira S. Ashour,Simon James Fong,Chintan Bhatt Pdf

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

Analytics in Healthcare

Author : Christo El Morr,Hossam Ali-Hassan
Publisher : Springer
Page : 105 pages
File Size : 43,5 Mb
Release : 2019-01-21
Category : Medical
ISBN : 9783030045067

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Analytics in Healthcare by Christo El Morr,Hossam Ali-Hassan Pdf

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.

Data Science and Medical Informatics in Healthcare Technologies

Author : Nguyen Thi Dieu Linh,Zhongyu (Joan) Lu
Publisher : Springer Nature
Page : 91 pages
File Size : 44,8 Mb
Release : 2021-06-19
Category : Technology & Engineering
ISBN : 9789811630293

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Data Science and Medical Informatics in Healthcare Technologies by Nguyen Thi Dieu Linh,Zhongyu (Joan) Lu Pdf

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.

Artificial Intelligence and Big Data Analytics for Smart Healthcare

Author : Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui
Publisher : Academic Press
Page : 292 pages
File Size : 54,9 Mb
Release : 2021-10-22
Category : Medical
ISBN : 9780128220627

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Artificial Intelligence and Big Data Analytics for Smart Healthcare by Miltiadis Lytras,Akila Sarirete,Anna Visvizi,Kwok Tai Chui Pdf

Artificial Intelligence and Big Data Analytics for 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 in Healthcare

Author : Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki
Publisher : Springer Nature
Page : 187 pages
File Size : 49,8 Mb
Release : 2019-10-01
Category : Technology & Engineering
ISBN : 9783030316723

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Big Data Analytics in Healthcare by Anand J. Kulkarni,Patrick Siarry,Pramod Kumar Singh,Ajith Abraham,Mengjie Zhang,Albert Zomaya,Fazle Baki Pdf

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.

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

Author : Noughabi, Elham Akhond Zadeh,Raahemi, Bijan,Albadvi, Amir,Far, Behrouz H.
Publisher : IGI Global
Page : 545 pages
File Size : 52,5 Mb
Release : 2017-07-20
Category : Computers
ISBN : 9781522525165

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Handbook of Research on Data Science for Effective Healthcare Practice and Administration by Noughabi, Elham Akhond Zadeh,Raahemi, Bijan,Albadvi, Amir,Far, Behrouz H. Pdf

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.

How Data Science Is Transforming Health Care

Author : Tim O'Reilly,Mike Loukides,Julie Steele,Colin Hill
Publisher : "O'Reilly Media, Inc."
Page : 13 pages
File Size : 40,7 Mb
Release : 2012-08-24
Category : Computers
ISBN : 9781449344979

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How Data Science Is Transforming Health Care by Tim O'Reilly,Mike Loukides,Julie Steele,Colin Hill Pdf

In the early days of the 20th century, department store magnate JohnWanamaker famously said, "I know that half of my advertising doesn'twork. The problem is that I don't know which half." That remainedbasically true until Google transformed advertising with AdSense basedon new uses of data and analysis. The same might be said about healthcare and it's poised to go through a similar transformation as newtools, techniques, and data sources come on line. Soon we'll makepolicy and resource decisions based on much better understanding ofwhat leads to the best outcomes, and we'll make medical decisionsbased on a patient's specific biology. The result will be betterhealth at less cost. This paper explores how data analysis will help us structure thebusiness of health care more effectively around outcomes, and how itwill transform the practice of medicine by personalizing for eachspecific patient.

Big Data Analytics for Intelligent Healthcare Management

Author : Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
Publisher : Academic Press
Page : 312 pages
File Size : 52,7 Mb
Release : 2019-04-15
Category : Science
ISBN : 9780128181478

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Big Data Analytics for Intelligent Healthcare Management by Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera Pdf

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