This work intends to an integration of implementing an automated diagnostic systems for breast cancer detection using Artificial Neural Network (ANN) in FPGA. In the world, breast cancer is the fifth most common cause of cancer death. So better classification system is needed for diagnosing breast cancer disease. In this work, the training and testing of the Multilayer Perceptron Neural Network (MLPNN) with Back Propagation Network (BPN) is done with the attributes of the record of the Wisconsin Breast Cancer Database (WBCD). The neural network lacks the flexibility during off line training. In order to overcome the flexibility, it is necessary to train and test the network on on-chip neural network using FPGA. The purpose is to determine the cancer of patients either having benign or malignant through an FPGA based implementation of smart instrument. In order to implement the hardware, VERILOG coding is done for ANN and synthesized by Xilinx family XC5VLX50TFFT1136 FPGA Virtex 5 board using XILINX ISE tool to get the netlist of ANN. Finally the netlist is mapped to FPGA and the hardware functionality is verified. The correct classification rate of proposed system is 90.83%.