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Why Physician's Keep Coming Back to Telemedicine: Predicting Using Unsupervised Learning

Telemedicine for health care delivery is growing at an explosion rate. The Theory of Planned Behaviour (TPB) model is extended to determine the predictors of adoption of telemedicine by physicians and explaining the importance of predictors. An Unsupervised learning model which is nonlinear is developed to understand the predictors of adoption of telemedicine. 145 physicians’ using telemedicine were randomly sampled and surveyed. Neural network analysis was used to predict the adoption of telemedicine by physicians and the model was compared with the result of supervised learning using regression analysis. The neural network outperformed the regression model and established the non linear relationship between different predictors found significant. The framework offers an integrated view, taking into account the predictors, for physicians in explaining and validating the predictor's importance. The findings suggest that the proposed model offer a deeper understanding of the predictors that influence the adoption of telemedicine. Behavioral intention is high when they are associated with other predictors.