Abstract:
The diagnosis of diseases is a critical
anddifficult job in medicine. An attempt to exploit
knowledge and experience of several specialists
and clinical screening data of patients composed
in databases to assist the diagnosis procedure.
Data Mining is the process of automating
information discovery for finding relationships
data to predict outcomes. In this paper, an
efficient approach is compared for the intelligent
diseases prediction based on Back Propagation
Neural Network (BPNN) and Probabilistic Neural
Network (PNN) techniques. This paper will
compare the performance of BPNN and PNN
based on their accuracy and execution time for
predicting the diseases such as chronic kidney
disease, hepatitis disease, heart disease and breast
cancer disease
