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Pattern and Data Analysis in Healthcare Settings

Book Description

Business and medical professionals rely on large data sets to identify trends or other knowledge that can be gleaned from the collection of it. New technologies concentrate on data’s management, but do not facilitate users’ extraction of meaningful outcomes. Pattern and Data Analysis in Healthcare Settings investigates the approaches to shift computing from analysis on-demand to knowledge on-demand. By providing innovative tactics to apply data and pattern analysis, these practices are optimized into pragmatic sources of knowledge for healthcare professionals. This publication is an exhaustive source for policy makers, developers, business professionals, healthcare providers, and graduate students concerned with data retrieval and analysis.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Foreword
  6. Preface
    1. TARGET AUDIENCE
  7. Acknowledgment
  8. Section 1: Healthcare Settings and Security
    1. Chapter 1: Action Rules Mining in Hoarseness Disease
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. NEW COMPUTER SUPPORTED DIAGNOSIS SYSTEM
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    2. Chapter 2: Secure Storage and Transmission of Healthcare Records
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SECURE STORAGE OF HEALTH RECORDS
      5. MAIN FOCUS OF THE CHAPTER
      6. DEFINITIONS FOR THE PROPOSED SYSTEM
      7. KEY DEPENDENT DYNAMIC S-BOX FUNCTION
      8. DUAL ENCRYPTION METHOD
      9. FUTURE RESEARCH DIRECTIONS
      10. CONCLUSION
      11. REFERENCES
      12. KEY TERMS AND DEFINITIONS
    3. Chapter 3: Fast Medical Image Segmentation Using Energy-Based Method
      1. ABSTRACT
      2. INTRODUCTION
      3. MAIN FOCUS OF CHAPTER
      4. SUMMARY
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    4. Chapter 4: Towards Parameterized Shared Key for AVK Approach
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND OF KEY SIZE SELECTION PROBLEM
      4. MAIN FOCUS OF THE CHAPTER
      5. PARAMETERS ONLY SCHEME FOR AUTOMATIC VARIABLE KEY
      6. EVALUATION OF CRYPTOSYSTEM: HACKERS / CRYPTANALYST PERSPECTIVE
      7. CONCLUSION
      8. FUTURE RESEARCH DIRECTIONS
      9. REFERENCES
    5. Chapter 5: Innovative Approach for Improving Intrusion Detection Using Genetic Algorithm with Layered Approach
      1. ABSTRACT
      2. INTRODUCTION
      3. INTRUSION DETECTION SYSTEMS (IDS)
      4. IDS TECHNOLOGIES
      5. IDS MODELS
      6. KDD DATASET
      7. BACKGROUND
      8. FITNESS FUNCTION FOR ACCURACY
      9. MAIN FOCUS OF THE CHAPTER
      10. RESULTS
      11. CONCLUSION
      12. FUTURE RESEARCH DIRECTIONS
      13. REFERENCES
      14. KEY TERMS AND DEFINITIONS
  9. Section 2: Knowledge Visualization and Big Data
    1. Chapter 6: Knowledge Extraction from Domain-Specific Documents
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. RELATED WORK
      5. MAIN FOCUS OF THE CHAPTER
      6. SOLUTIONS AND RECOMMENDATIONS
      7. DOMAIN KNOWLEDGE ACQUISITION FOR BUILDING ONTOLOGY
      8. FURTHER RESEARCH DIRECTIONS
      9. CONCLUSION
      10. REFERENCES
      11. KEY TERMS AND DEFINITIONS
    2. Chapter 7: Semi-Automatic Ontology Design for Educational Purposes
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FURTHER RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 8: Improving Multimodality Image Fusion through Integrate AFL and Wavelet Transform
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUZZY SET THEORY AND FUZZY LOGIC
      7. SOLUTION AND RECOMMENDATION
      8. FUTURE RESEARCH DIRECTION
      9. REFERENCES
      10. KEY TERMS AND DEFINITIONS
    4. Chapter 9: Big Data
      1. ABSTRACT
      2. INTRODUCTION
      3. HADOOP DISTRIBUTED FILE SYSTEM (HDFS)
      4. MAP REDUCE: A PROGRAMMING PARADIGM
      5. THE DAWN OF NOSQL AS A SOLUTION FOR HANDLING BIG DATA
      6. HOW NOSQL DATABASES DIFFER FROM TRADITIONAL RELATIONAL DATABASE?
      7. NEED OF NOSQL DATABASES
      8. WHAT NoSQL DATABASES CAN DO?
      9. AVAILABLE NoSQL DATABASES IN THE MARKET
      10. KEY-VALUE STORES
      11. DOCUMENT-ORIENTED DATABASES
      12. COLUMN STORE
      13. GRAPH DATABASE
      14. COMPARATIVE STUDY OF NOSQL DATABASES
      15. INTEGRATION OF NOSQL DATABASE
      16. ORACLE NOSQL DATABASE INTEGRATION
      17. APPLICATIONS OF NOSQL DATABASES
      18. FUTURE RESEARCH DIRECTIONS
      19. CONCLUSION
      20. REFERENCES
      21. KEY TERMS AND DEFINITIONS
  10. Section 3: Data Mining: Utilization and Application
    1. Chapter 10: Bombay Stock Exchange of India
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. ASSOCIATION RULE MINING
      7. EXPERIMENTAL RESULTS
      8. ARTIFICIAL NEURAL NETWORK (ANN)
      9. CONCLUSION
      10. FUTURE RESEARCH DIRECTIONS
      11. REFERENCES
      12. KEY TERMS AND DEFINITIONS
    2. Chapter 11: Profit Pattern Mining Using Soft Computing for Decision Making
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND: A BRIEF REVIEW OF THE WORK ALREADY DONE
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. CONCLUSION
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    3. Chapter 12: Effect of Odia and Tamil Music on the ANS and the Conduction Pathway of Heart of Odia Volunteers
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. MATERIALS AND METHODS
      6. RESULT AND DISCUSSION
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
      9. REFERENCES
      10. ADDITIONAL READING
      11. KEY TERMS AND DEFINITIONS
    4. Chapter 13: Document Clustering
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTION
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    5. Chapter 14: Cluster Analysis with Various Algorithms for Mixed Data
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ANALYSIS AND REPRESENTATION OF DATA
      5. CONCLUSION
      6. FUTURE WORK
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
  11. Compilation of References
  12. About the Contributors