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A Model in Recommender Systems for Disease Diagnosis Using Combined Method

Author Affiliations

  • 1IslamicAzadUniversity south TehranBranch, Tehran, IRAN
  • 2Iran University of Science and Technology, Tehran, IRAN

Res. J. Recent Sci., Volume 3, Issue (3), Pages 72-77, March,2 (2014)


Diagnosis of dieses is always of the concerns for physicians. Since wrong diagnosis of diseases especially in diseases leading to surgery would have unpleasant consequences, it was attempted to offer a model of data mining models so that physicians are aided in diagnosis of diseases. To this end, considering some disease have very similar symptoms and there is the highest probability of wrong diagnosis by the physician about them, data mining is used for an appropriate solution. Hence, 6 diseases were selected with are treated by surgery and have similar symptoms in diagnosis. After medical data collection in 550 patients and purification of 50 cases, the number of patients was reduced to 500. Then data were divided into 5 groups by reviewing medical literature and recognizing important of attributes in symptoms of diseases. This division was based on the fact that a group of data has different impact on the designed model compared to the other group. This database was implemented in Clementine software in categorization, clustering and partitioning methods and the best method was evaluated. Then a combined method (including partitioning and categorization and also categorization and clustering and partitioning) was developed as the final model. The final model in both combined methods offers the best diagnosis for aid of physician with evaluation percentage 96.99.


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