You are required to do a literature review for attached 12 articles by following the below report structure: Introduction: Provide some background about the topic, the motivation for the literature review, purpose statement and the roadmap of the report.

DATA MINING IN HEALTHCARE
October 23, 2019 Off All,

You are required to do a literature review for attached 12 articles by following the below report structure: Introduction: Provide some background about the topic, the motivation for the literature review, purpose statement and the roadmap of the report. Summarize The Literature: Discuss the major themes found in the articles with a clear taxonomy/classification, discuss the used research methods, discuss the differences and similarities between the papers and discuss what you have learnt from summarizing all papers and your analytical view on them. Linkage with The Practical State of the Art: Provide an overview about the technological state-of-the-art in the domain of the topic (e.g., market overview, major companies, main software, popular case studies) in addition to projecting this view on the Saudi status, if applicable. Conclusion: What was important about your study, what did you find out that was new to you and how would you expand the work in the future. The maximum accepted Turnitin percentage is 20%. List of articles : 1. Clinical data mining 2. Concurrence of big data analytics and healthcare: A systematic review 3. Data Mining and Information Retrieval in the 21st century: A bibliographic review 4. Data Mining in Healthcare – A Review 5. Data work in healthcare: An Introduction 6. Medical informatics research trend analysis: A text mining approach. 7. Mining and exploring care pathways from electronic medical records with visual analytics. 8. Mining Electronic Health Records (EHRS): A Survey. 9. Process mining in healthcare: A literature review 10. Studies in the use of data mining, prediction algorithms, and a universal exchange and inference language in the analysis of socioeconomic health data. 11. Systematic mapping study of data mining-based empirical studies in cardiology 12. Veracity in big data: How good is good enough