What is it about?
In this project both descriptive and predictive analytic tools were used, and a fraud detection suite was developed for healthcare insurance companies based on real life private insurance transactional data.
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Why is it important?
In real-life data analytics projects, the approach of simply “sending data and waiting for results” is often insufficient. It requires combining domain expertise with machine learning methods, where domain experts propose new models based on insights uncovered by machine learning. That is to say, interaction between the human an machine takes place. This paper, which is based on real life problem faced by a company, is among the first examples where interactive machine learning in healthcare is reported.
Perspectives
This paper, which is based on real life problem faced by a company, is among the first examples where interactive machine learning in healthcare is reported.
Prof. Kemal Kilic
Sabanci Universitesi
Read the Original
This page is a summary of: An interactive machine-learning-based electronic fraud and abuse detection system in healthcare insurance, Applied Soft Computing, November 2015, Elsevier,
DOI: 10.1016/j.asoc.2015.07.018.
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