A robust validation framework for trend mining : a study in diabetic retinopathy

Data mining is concerned with the identification of hidden patterns in data. Trand mining is a branch of data mining that focusses on the process to identify and analyze hidden trends in temporal data. A novel trend mining framework is described in this paper. The framework considers trends in terms of sequences of support values associate with frequent items sets and uses a trend mining algorithm that produces prototypes trends. To validate the framework in the analysis of the generated trends a mechanism is also proposed. The framework is evaluated using longitudinal Diabetic Retinopathy screening data.