Big data analytics in healthcare / Anand J. Kulkarni, Patrick Siarry, Pramod Kumar Singh, Ajith Abraham, Mengjie Zhang, Albert Zomaya, Fazle Baki, editors.

Format:

Book

Contributor:

Kulkarni, Anand Jayant.

Siarry, Patrick.

Siṃha, Pramoda Kumāra.

Abraham, Ajith, 1968-

Zhang, Mengjie.

Zomaya, Albert Y.

Baki, Fazle.

ProQuest ebook central.

Series:

Studies in big data ; v. 66.

Studies in Big Data ; v. 66

Language:

English

Subjects (All):

Big data.

Medical informatics.

Physical Description:

1 online resource (193 pages).

Place of Publication:

Cham : Springer, [2020]

System Details:

text file

Contents:

Intro; Preface; First Part: Challenges, Opportunities, Platforms, and Tools of Big Data in Healthcare; Second Part: Mathematical Modeling and Solutions, Big Data Applications, and Platforms; Contents; Challenges, Opportunities, Platforms and Tools of Big Data in Healthcare; Big Data Analytics and Its Benefits in Healthcare; 1 Introduction; 2 Introduction to Big Data; 2.1 Processing of Big Data; 2.2 Introduction to Hadoop; 2.3 Hadoop Architecture; 2.4 How Does Hadoop Works?; 2.5 Advantage of Hadoop; 2.6 HDFS in Healthcare; 3 Big Data in Healthcare; 3.1 Mobile Big Data; 3.2 Big Data Analytics

3.3 Big Data Ecosystem for Healthcare [8]3.4 Big Data Life Cycle; 3.5 Need for Big Data Analytics in Healthcare; 4 Advantages of Big Data [7]; 4.1 Issues in Big Data; 4.2 Examples of Big Data Analytics for Healthcare; 4.3 Applications of Big Data in Healthcare; 5 Conclusions and Future Scope; References; Elements of Healthcare Big Data Analytics; 1 Introduction; 2 Challenges in Application of Big Data Analytics for Healthcare; 2.1 Data and Process-Related Challenges; 2.2 Manpower-Related Challenges; 2.3 Domain-Related Challenges; 2.4 Managerial/Organizational Challenges

3 Key Elements of Big Data Analytics in Healthcare3.1 Data Inputs; 3.2 Functional Elements; 3.3 Human Element; 3.4 Security Elements; 4 Foundational Steps of Big Data Analytics Program; 4.1 Strategic Roadmap; 4.2 Lucid Business Case; 4.3 Requisite Resources; 4.4 Explicit Roles and Responsibilities; 4.5 Right Data Architecture; 4.6 Appropriate Tools and Technologies; 4.7 Data Governance and Standards; 4.8 Legacy Migration; 4.9 Executive Support; 4.10 Organizational Adoption; 4.11 Analytics and Reporting; 4.12 Insights and Interpretation; 5 Future Directions; 6 Conclusion; 7 Summary Points

2.2 Apache Spark3 Applications; 3.1 Healthcare; 3.2 Public Sector; 4 Conclusion; References; Big Data in Healthcare: Technical Challenges and Opportunities; 1 Introduction; 2 Big Data in Healthcare; 3 Types of Big Data; 3.1 Structured Data; 3.2 Unstructured Data; 3.3 Semi-structured Data; 4 Big Data Characteristics; 4.1 Volume; 4.2 Variety; 4.3 Velocity; 4.4 Veracity; 4.5 Variability; 4.6 Value; 5 Analyzing Big Data; 5.1 Predictive Analysis; 5.2 Prescriptive Analysis; 5.3 Diagnostic Analysis; 5.4 Descriptive Analysis; 6 Challenges in Big Data Healthcare; 7 Technical Challenges

Notes:

Electronic reproduction. Ann Arbor, MI Available via World Wide Web.

Print version record.

ReferencesBig Data in Supply Chain Management and Medicinal Domain; 1 Introduction; 1.1 Characteristics of Big Data; 1.2 Big Data Analytics; 2 Big Data in Supply Chain Management; 2.1 Traditional Analytics and Big Data Analytics; 2.2 Landscapes of Supply Chain; 2.3 Big Data Platforms; 2.4 Impending Methodologies; 3 Big Data in Medicinal Domain; 3.1 Process Flow; 3.2 Contemporary Methodologies/Case Studies; 4 Conclusion; References; A Review of Big Data and Its Applications in Healthcare and Public Sector; 1 Introduction; 1.1 5 V's of Big Data; 2 Big Data Technologies; 2.1 Hadoop.

7.1 Data Integration

Other Format:

Print version: Kulkarni, Anand J. Big Data Analytics in Healthcare.

ISBN:

9783030316723

3030316726

Publisher Number:

99982569953

Access Restriction:

Restricted for use by site license.