At present, regional differences in medical standards, different levels of hospital doctors, and the same doctor making the diagnosis of different conditions have different clinical not inevitably lead to high levels of medical experts to ensure a stable team and good medical facilities, and for a large number have been confirmed cases have to be better utilized.
In order to better diagnosis of diabetes and its complications and treatment, the paper carried out exploratory rough set theory in diagnosis of diabetes research, an expert for the good use of confirmed cases, clinicians assisted diagnosis, improve the diagnosis as soon as possible and do more diagnosis and treatment of diabetes, to promote the positive significance to human health.The main work, and this contribution: first, diagnosed diabetes patients through data collection and pretreatment and thus based on rough set theory is applied to provide effective diagnostic analysis of diabetes data sources;.Second, based on rough set methods and diagnostic mode of thinking according to medical experts, including methods proposed to rough, rough rough exclusion laws and contrast method to extract diagnosis rules diagnosed diabetes cases, results show that the correct rate of 97.6%;.Third, according to medical clinical practice, that clinical false positive and false negative phenomena, different doctors in the diagnosis requirements are different, the common complications of diabetes and sex, as well as a variety of complications of diabetes and other factors may be concurrent proposed Law Degree with false content matching rules to reduce leakage sense misdiagnosed;.Fourth, the above rule-based extraction and analysis of the results, based on clinical diagnosis in accordance with the needs of the diagnosis model was designed, developed diagnosis system, experiments show that the proposed method is feasible and effective, system test results can assist clinicians to diagnose the effect of the complications of diabetes.
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