Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
Group decision support with the analytic hierarchy process
Decision Support Systems
Data mining and KDD: promise and challenges
Future Generation Computer Systems - Special double issue on data mining
Knowledge discovery techniques for predicting country investment risk
Computers and Industrial Engineering
Data mining issues and opportunities for building nursing knowledge
Journal of Biomedical Informatics - Special issue: Building nursing knowledge through infomatics: from concept representation to data mining
Expanding self-organizing map for data visualization and cluster analysis
Information Sciences: an International Journal - Special issue: Soft computing data mining
A database clustering methodology and tool
Information Sciences—Informatics and Computer Science: An International Journal
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A comparative analysis of an extended SOM network and K-means analysis
International Journal of Knowledge-based and Intelligent Engineering Systems
Intelligent profitable customers segmentation system based on business intelligence tools
Expert Systems with Applications: An International Journal
Auto claim fraud detection using Bayesian learning neural networks
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Multi-agent system for customer relationship management with SVMs tool
International Journal of Intelligent Information and Database Systems
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Health expenditures have rapidly risen to the top of the political agenda in many countries. Physicians and their actions account for most health care spending. However, very few studies have attempted more comprehensive exploration of general practitioners' (GPs') practice patterns segmentation. This paper seeks to bridge this gap. It facilitates the payer or stakeholder to use these GPs' practice patterns and features to detect inappropriate or unusual behavior to overcome the growth in health expenditures. This study uses knowledge discovery in database (KDD) to segment the general practitioners' (GPs') profiles by carrying out clustering techniques based on the features of expenditures, and then builds health expenditure information to support decision makers in the management of various GP's practice patterns. It draws a complete picture relating to the health expenditures characteristics of GPs' practice patterns by reducing the attributes space to a smaller number of dimensions. Effective segmentation of GPs' practice patterns makes it easier to detect and investigate health fraud by recognizing and quantifying the features of claims and providers.