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An improved medical decision support system for classification of Cardiac Disease using Multiclass Neural Network Classifier (MNN) is developed for Cardiac disease prediction presented in this paper. The ECG signal datasets are preprocessed and filtered by Butterworth noise filtering for removing the measurement noise and extracted peaks was obtained for extraction using Peak difference method. The detected feature peaks are used to perform classification and evaluation using Multiclass Neural network training. The generated training patterns from the preprocessed signal are used as input and from the data set the pre-computed pattern set is retrieved. With the extracted peak feature, compute each ECG wave similarity measure with the available pattern set database. The Multiclass pattern set which has more similarity in each pattern is identified and based on identified values of each signal values the …