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Crystal Ball
Management Information System for the Information Age
November 17, 2011
Dropbox Assignment 4: Crystal Ball, Clairvoyant, Fortune Telling . . . Can Predictive Analytics Deliver the Future?

1. Many predictive analytic models are based on neural network technologies. What is the role of neural networks in predictive analytics? How can neural networks help predict the likelihood of future events. In answering these questions, specifically reference Blue Cross Blue Shield of Tennessee?
Predictive analytics can be helped with neural networks when there is a very large quantity of information available for examination. Neural networks examine literally thousands of bits of information to find relationships and patterns.
The likelihood of future events in neural networks are assisted by the fact that they can learn to adjust to new circumstances, lend themselves to parallel processing, function without having all the information or having that information in a structured format, copy with huge amounts to data with different variables, and analyze relationships found in the data
Blue Cross Blue Shield of Tennessee has a neural network which they use to predict health resources that will be needed after certain procedures. The patterns they find can help determine if a patient will have a reaction to the procedure. Having this data quickly can help save health care costs and patients. 2. What if the Richmond police began to add demographic data to its predictive analytics system to further attempt to determine the type of person (by demographic) who would in all likelihood commit a crime. Is predicting the type of person who would commit a crime by demographic data (ethnicity, gender, income level and so on) good or bad?
While demographics could be helpful in some situations, I think it is a bad idea at this present time. If the law enforcement uses this information to predict future crime, I believe it would open up a lot of controversy. Examining



Cited: Haag, Stephen and Maeve Cummings. Management Information Systems for the Information Age. 8th ed. New York: McGraw-Hill, 2010. Glenn, Linda. Genetic Testing to Predict Disease: Ethical, Legal, and Social Implications (ELSI). Dec 2007 ActionBioscience.org original article 10 Nov 2011

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