Big data analytics in healthcare. (©2020)

• Record Type: Book
• Further Information: Note: Anand J. Kulkarni, Patrick Siarry, Pramod Kumar Singh, Ajith Abraham, Mengjie Zhang, Albert Zomaya, Fazle Baki, editors.
• Other Names: Kulkarni, Anand Jayant; Siarry, Patrick; Singh, Pramod Kumar; Abraham, Ajith, 1968-; Zhang, Mengjie; Zomaya, Albert Y; Baki, Fazle
• 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
• Publisher Details: Cham : Springer
• Publication Date: 2020
• Copyright Date: 2020
• Extent: 1 online resource (193 pages)
• Subjects: 005.7; Big data; Medical informatics; Big data; Medical informatics; Electronic books
• Languages: English
• ISBNs: 9783030316723; 3030316726
• Related ISBNs: 9783030316716; 3030316718
• Notes: Note: 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; Note: Print version record.
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