Genomic Rule Based Diagnostic System

نویسندگان

  • Sofianita Mutalib
  • Shuzlina Abdul-Rahman
  • Azlinah Mohamed
چکیده

This paper presents a diagnostic system in determining diabetic disease using association rules generated from frequent pattern mining on genomic data. The diagnostic system facilitates biological information such as gene variants, gene information and phenotype data. Meanwhile, association rules revealed significant relationships between gene variants and condition of the individual. Besides that, the diagnostic system would be able to store and revised knowledge of analysis based on current findings. This could be further enhanced the integration of other physical symptoms and clinical data. The proposed system is expected to assist the medical practitioners to make better decision on the type of treatments suitable for patients.

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تاریخ انتشار 2014