A COMPARATIVE STUDY OF DATA MINING APPLICATIONS IN DIAGNOSING DISEASES

Data Mining has emerged as a technique of extracting and discovering new knowledge in data implicit in a large data warehouse so as to enable better decisions and strategy formulation. It is an effective and rapid process of data searching, retrieval and semantic analysis from different perspectives. Data mining helps in presenting and summarizing information extracted from data warehouse in a meaningful manner that can be used to increase business performance, enhance revenue and reduce costs. It is an ultimate process of finding patterns or correlations among relational databases. Data mining has revealed novel biomedical and healthcare acquaintances for clinical decision making that has great potential to improve the treatment quality of hospitals and increase the survival rate of patients. Disease diagnosis is one of the applications where data mining tools are establishing the successful results. This paper summarizes some techniques on medical diagnosis and prognosis. It has also been focused on current research being carried out using the data mining techniques to enhance the disease(s) forecasting process.