Abstract
Diabetes departments of hospitals provided more and more professional data from each case for data-driven learning. However, experts in hospitals argue that their experience can provide more reliable information than statistical data. This paper presents a Data-Experience intelligent model to predict the possibilities of diabetes complications with the occurrence of abnormal signs. The model merges data and experience mathematically by mixing human judging behavior from traditional Chinese medicine and statistical patient data from western medicine, which is under a particular situation. The probabilities given by the model can value the distributions of each diabetic complication while estimating the posterior when multi-abnormal signs occurred. An implement in a specific case is analyzed based on the statistical data and human judging performance, which shows the effectiveness and rationality of the Data-Experience Intelligent model for predicting diabetic complications proposed in this paper. The results give a more comprehensive prediction by synthesizing subjective information and objective information.
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