A single framework of precision surveillance of diabetes disease prognosis for better care with collaboration

Abstract

We present a decision support model for patient-centered precision surveillance that assists clinicians and patients for the whole disease prospect to provide a single operational framework of whole type 2 diabetic person care management while introducing experts in the loop modeling that facilitates data collection. Based on real-world data, the scientific computation shall be adopted with experts’ experiences for providing the patient health education and accessing complication risks thereby easily delineating disease pathways. A decision tree technique is used to build a single framework consisting of every possible diabetes complication in the decision process. Coping with the complex medical system for the prevention of diabetes and diabetic complications, a patient-centered framework gives the patient interactive, transparent and useful information for better communication in the decision process that includes experts’ experience as well as the value of the prediction generated from population-based data.