An Intelligent Fuzzy Transformation-Based Algorithm for Forecasting Patient Trust in Medical Centers

The purpose of this study is to investigate the nature of trust data in a service-oriented system (a public hospital) in the first step.After that we come up with time series of trust data to be predicted for future interactions. The verbal nature of trust in real world applications provides us to investigate it with a fuzzy approach. That’s why fuzzy transformation of data is adopted and its adequacy is compared with other two prediction approaches to verify our claims. To reach an acceptable and more accurate prediction, this study applies a fuzzy approach and more specifically fuzzy transformation approach. The next concern would be trust prediction as required data for continuing an interaction. Along with applying fuzzy transformation in the continuum for forecasting trust Values, we have applied artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). Then, performance of fuzzy transformation approach is compared based on the two methodologies and reported in the context of mean absolute percentage error (MAPE). Results verify that fuzzy transformation of data provides less error which validates our attitude toward subjectivity of data.

Keywords:

Trust Prediction , Hospital Management , Fuzzy Transformation , Simulation , Artificial Neural network (ANN) , Adaptive Network Based Inference System (ANF IS)