Adv DBs: A possible future project?

Below is a possible future research paper on a database related subject.

Title: Using MapReduce to aid in clinical test utilization patterns in the medicine

The motivation:

Efficient processing and analysis of clinical data could aid in better clinical tests on patients, and MapReduce solutions allow for an integrated solution in the medical field, which aids in saving resources when it comes to moving data in and out of storage.

The problem statement (symptom and root cause)

The rates of Sexually Transmitted Infections (STIs) are increasing at alarming rates, could the addition of Roper Saint Francis Clinical Network in the South test utilization patterns into Hadoop with MapReduce reveal patterns in the current STIs population and predict areas where an outbreak may be imminent?

The hypothesis statement (propose a solution and address the root cause)

H0: Data mining in Hadoop with MapReduce will not be able to identify any meaningful pattern that could be used to predict the next location for an STI outbreak using clinical test utilization patterns.

H1: Data mining in Hadoop with MapReduce can identify a meaningful pattern that could be used to predict the next location for an STI outbreak using clinical test utilization patterns.

The research questions

Could this study apply to STIs outbreaks rates be generalized into other disease outbreak rates?

Is this application of data-mining in Hadoop with MapReduce the correct way to analyze the data?

The professional significance statement (new contribution to the body of knowledge)

Identifying where an outbreak of any disease (or STIs), via clinical tests utilization patterns has yet to be done according to Mohammed et al (2014), and they have stated that Hadoop with MapReduce is a great tool for clinical work because it has been adopted in similar fields of medicine like bioinformatics.

Resources

  • Mohammed, E. A., Far, B. H., & Naugler, C. (2014). Applications of the MapReduce programming framework to clinical big data analysis: Current landscape and future trends. Biodata Mining, 7. doi:http://dx.doi.org/10.1186/1756-0381-7-22 – Doctoral Library Advanced Technologies & Aerospace CollectionPokorny, J. (2011).
  • NoSQL databases: A step to database scalability in web environment. In iiWAS ’11 Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services (pp. 278-283). – Doctoral Library ACM Digital Library

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