Instance-Based Learning Algorithms
Machine Learning
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A prescription fraud detection model
Computer Methods and Programs in Biomedicine
Mining medical specialist billing patterns for health service management
AusDM '08 Proceedings of the 7th Australasian Data Mining Conference - Volume 87
Discovering inappropriate billings with local density based outlier detection method
AusDM '09 Proceedings of the Eighth Australasian Data Mining Conference - Volume 101
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K-nearest neighbour (KNN) algorithm in combination with a genetic algorithm were applied to a medical fraud detection problem. The genetic algorithm was used to determine the optimal weighting of the features used to classify General Practitioners' (GP) practice profiles. The weights were used in the KNN algorithm to identify the nearest neighbour practice profiles and then two rules (i.e. the majority rule and the Bayesian rule) were applied to determine the classifications of the practice profiles. The results indicate that this classification methodology achieved good generalisation in classifying GP practice profiles in a test dataset. This opens the way towards its application in the medical fraud detection at Health Insurance Commission (HIC).