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- W2240546010 abstract "Diabetes is a constitutional disease, which is an outcome of leading a sedentary life and eating processed foods like biscuits, bread, cakes, chocolates, pudding, ice cream, etc. Case-Based Reasoning (CBR) has a library of solved cases which helps to diagnose the unsolved diabetic cases. Each case describes the problem, solution and outcome of the same. Whenever similar situations occur, the relevant cases are retrieved from the library and utilized for the diagnosis of diabetes. Ontology contains information about diabetes - symptoms, causes, different types of diabetes and also the type of diagnosis - which helps in effective system-level reasoning. While Fuzzy Logic (FL) is used for item-level reasoning. Based on the relevant count of the symptoms, ontology is analyzed with inputs, the relevant diagnosis report is retrieved from the ontology and repaired, and existing cases are revised and retained in the case library for future use. The approach presented in this paper is to reason from the facts and determine whether the patients are suffering from diabetes or not." @default.
- W2240546010 created "2016-06-24" @default.
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- W2240546010 date "2009-09-25" @default.
- W2240546010 modified "2023-09-23" @default.
- W2240546010 title "Role of Ontology in Case-Based Reasoning (CBR) for Diagnosing Diabetes" @default.
- W2240546010 hasPublicationYear "2009" @default.
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