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Handbook of research on engineering, business, and healthcare applications of data science and analytics
Research on engineering, business, and healthcare applications of data science and analytics
Chapter 1. Introduction to data science -- Chapter 2. A walk through the world of data analytics -- Chapter 3. A survey on tools for data analytics and data science -- Chapter 4. Tools, technologies, and methodologies to support data science: support technologies for data science -- Chapter 5. A survey on intelligence tools for data analytics -- Chapter 6. Data analysis in context-based statistical modeling in predictive analytics -- Chapter 7. Evaluating business performance using data envelopment analysis and grey relational analysis -- Chapter 8. Comparison of European option pricing models at multiple periods -- Chapter 9. Use of data analytics to increase the efficiency of last mile logistics for ecommerce deliveries -- Chapter 10. Review of big data applications in finance and economics -- Chapter 11. Role of data science and data analytics in forensic accounting and fraud detection -- Chapter 12. Machine learning and its application in monitoring diabetes mellitus -- Chapter 13. Opportunistic edge computing architecture for smart healthcare systems -- Chapter 14. Risk analysis of diabetic patient using map-reduce and machine learning algorithm -- Chapter 15. Integrated big data e-healthcare solutions to a fragmented health information system in Namibia -- Chapter 16. Technology in healthcare: vision of smart hospitals -- Chapter 17. Gait abnormality detection using deep convolution network -- Chapter 18. Exploration of computational intelligence insights and data analytics to combat COVID-19 -- Chapter 19. Computer-aided diagnosis of knee osteoarthritis from radiographic images using random forest classifier -- Chapter 20. Healthcare conversational chatbot for medical diagnosis -- Chapter 21. A literature review on thyroid hormonal problems in women using data science and analytics: healthcare applications -- Chapter 22. Influence of some sociodemographic factors on causes of death among South African youth -- Chapter 23. Information technology act 2000 and the potential use of data analytics in reducing cybercrime in India -- Chapter 24. Clustering by K-means method and K-medoids method: an application with statistical regions of Turkey -- Chapter 25. Descriptive data analytics on dinesafe data for food assessment and evaluation using R programming language: a case study on Toronto's dinesafe inspection and disclosure system.
Bhushan Patil and Manisha Vohra [editors].
Includes bibliographical references and index.
Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]
Advances in data mining and database management (ADMDM) book series