Abnormal Drug Reaction Finding using Temporal Nodes Bayesian Model

Drugs are frequently prescribed to patient’s with the aim of improving each patient’s medical state. But unfortunately most of the drugs produce undesirable side effects. The ADR method is not possible to investigate all the different drug combinations. The proposed system analyze the best drug and cross drug reaction and its symptoms based on association and temporal model. The proposed technique applies a prediction method with the existing temporal nodes Bayesian Model (TNBM) to data extracted from the patient and drug database in order to explore the probabilistic and best relationships between drug resistance mutations. Improving the classification and prediction accuracy, mutation and cross over functionalities has been proposed. The data mining algorithm CADR was developed to analyze the best and worst drug and drug pairs based on their casual and irregular reactions over a real electronic patient’s database.