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Handbook of research on engineering, business, and healthcare applications of data science and analytics / Bhushan Patil and Manisha Vohra, editors.
EBSCOhost Academic eBook Collection (North America) Available online
EBSCOhost Academic eBook Collection (North America)- Format:
- Book
- Series:
- Advances in data mining and database management (ADMDM) book series.
- Advances in data mining and database management (ADMDM) book series, 2327-199X
- Language:
- English
- Subjects (All):
- Information resources--Data processing.
- Analytical chemistry--Quantitative.
- Big data.
- Engineering--Data processing.
- Business--Data processing.
- Medical care--Data processing.
- Physical Description:
- 33 PDFs (583 pages)
- Other Title:
- Research on engineering, business, and healthcare applications of data science and analytics
- Place of Publication:
- Hershey, PA : IGI Global, [2021]
- System Details:
- Mode of access: World Wide Web.
- Summary:
- "This book explores the application of data science and analytics in the engineering, healthcare, and business sectors"-- Provided by publisher.
- Contents:
- 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.
- Notes:
- Description based on print version record.
- Includes bibliographical references and index.
- ISBN:
- 1-7998-3054-3
- OCLC:
- 1126349115
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