Analysis Cataract Patients Databases for Bioinformatics

  • Authors

    • Zaki .S. Tywofik
    • Abdul Karem Thamer Mohammed
    https://doi.org/10.14419/ijet.v7i2.9.9392
  • Data Mining, Classification, Decision Tree Algorithm, Weka tool

  • Abstract

    The aims at using data mining in the data of Cataract derived from the report prepared by sample for many females and males the  Health Organization to suggest the most effective ways to treat Cataract according to the age-old. Believe that the expected results of the research will be of medical benefit for Oral or Insulin for two main reasons. Doctors usually do not have the time or the good enough to scrutinize a large number of data to derive new rules for treatment, and therefore the use of data mining will extract the rules and the rules of the doctors. A cataract can cause a decline in visual capacity, which thus can be named a visual inability. Cataracts can be characterized in three different ways. The main definition is a target focal point change. The second is a focal point haziness that is related with a characterized dimension of visual sharpness misfortune. The third identifies with the useful results of focal point placations. This rule centers around the last definition. It manages care of the patient with useful disability because of Cataracts and enhancement in capacity because of treatment for the condition. Considering the pervasiveness of cataract among male and female the investigation is gone for discovering the attributes that decide the nearness of cataract and to follow the greatest number of people experiencing cataract test of 18 people. In this paper the information characterization is Cataracts patients informational collection is created by gathering information from doctor's facility.   

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  • How to Cite

    Tywofik, Z. .S., & Mohammed, A. K. T. (2018). Analysis Cataract Patients Databases for Bioinformatics. International Journal of Engineering & Technology, 7(2.9). https://doi.org/10.14419/ijet.v7i2.9.9392