Health preventive medical evaluation programs are strategies commonly implemented as part of national health prevention efforts. Two problems related with the implementation of such strategies are subject profiling and medical test selection. The amount of different types of information that have to be analyzed by physicians in the screening for pathologies and medical test prescription can be overwhelming and significantly increases the complexity of this problem. Two decision-tree-based approaches are proposed in this study for subject profiling and medical test rationing. The proposed models perform well in terms of prediction. Results show that the implementation of these approaches helps to profile consultants into healthy and unhealthy subjects which can be used to ration medical test and design policies for preventive health evaluation programs.
