Diabetes Prediction Data Model using Big Data Technologies

The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for the need of patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. In Today's world many different people are in need of healthcare at the finest and quickest way possible, to make this possible our application does a critical analysis of the people's profile and comes up with the nearest hospital that could treat the patient the best way possible in terms of Finance, Disease that the patient is diagnosed with. Using this application, the patient enters his basic Information with the added details of the symptoms, allergies or specifically stating to which disease he needs treatment in order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. In turn, the Application does a big data analysis using Hadoop and reduces the result to the best possible solution consisting of hospitals situated the nearest to the patient that meets all his requirements inclusive of his financial status. Citation: Naveen Raja S. R, Licet; Aswin Kumar. V ,Licet; Richard Paul. V ,; Ms. Shobana. G ,Licet; Dr. D. Doreen Hephzibah Miriam ,CIRF. "Diabetes Prediction Data Model using Big Data Technologies." Global Research and Development Journal For Engineering : 1 - 4.