Modeling perceiving of recommendations provided by clinical decision support system based on predictive modeling within dental preventive screening

Abstract

The results of a current study of the perception of clinical decision support systems (CDSS) in the framework of preventive screening by dentists in schools of the Russian Ministry of Defense (cadet corps) are presented. Using the example of the scenario under consideration, a prototype of the CDSS based on machine learning was evaluated. To assess perception, a survey was conducted demonstrating the results of the prototype and assessing the perceived characteristics of the provided predictive modeling results. A model was built based on a Bayesian network to evaluate the considered indicators, which demonstrated an increase in the quality of prediction of perceived indicators, taking into account the influence of latent states of the operator’s subjective perception. The proposed approach is planned to be used in the future to increase the efficiency of doctor-CDSS interaction.

Keywords

• decision support systems
• human-computer interaction
• predictive modeling
• machine learning
• caries
• preventive screening