It has been proposed that social determinants play a role in identifying the type of person likely to develop Type 2 diabetes. Social attributes such as highest education level achieved, family history or place of residence and/or birth, all play a strong role in the probability of a person developing Type 2 diabetes later in life. Social determinants should therefore be able to be used to build a knowledge base (KB) as a part of a decision support system (DSS) for Type 2 diabetes prediction. The results of the current research are promising. The decision support system (DSS) created using Ripple Down Rules (RDRs) achieved an accuracy of 84.5%, a specificity of 92.3% and a sensitivity of 46% using 79 RDRs.
Omar, Adel; Beydoun, Ghassan; Win, Khin Than; and Jelinek, Herbert, "The Incremental Development of a Diabetes 2 Knowledge Base System using Ripple Down Rules" (2022). PACIS 2022 Proceedings. 18.
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