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Discovering Diabetes Complications: an Ontology Based Model

Tahani Daghistani, Riyad Al Shammari, Muhammad Imran Razzak.

Cited by (1)

Abstract
Background: Diabetes is a serious disease that spread in the world dramatically. The diabetes patient has an average of risk to experience complications. Take advantage of recorded information to build ontology as information technology solution will help to predict patients who have average of risk level with certain complication. It is helpful to search and present patient’s history regarding different risk factors. Discovering diabetes complications could be useful to prevent or delay the complications. Method: We designed ontology based model, using adult diabetes patients’ data, to discover the rules of diabetes with its complications in disease to disease relationship. Result: Various rules between different risk factors of diabetes Patients and certain complications generated. Furthermore, new complications (diseases) might be discovered as new finding of this study, discovering diabetes complications could be useful to prevent or delay the complications. Conclusion: The system can identify the patients who are suffering from certain risk factors such as high body mass index (obesity) and starting controlling and maintaining plan.

Key words: Protégé, ontology, SPARQL, rules, diabetes, complications



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