Smart diagnosis of long bone tumor / Mazni Parimin - Parimin, Mazni (Faculty of Information Technology and Quantitative Sciences, 2005)
This project is about diagnosing the long bone tumor using backpropagation neural network. The main purpose of this project is to construct artificial neural network model that can be used to diagnose the long bone tumor and to implement the artificial neural network model into the design of the prototype. The construction of this prototype consist of neural network training and testing process, where the backpropagation training algorithm are used to recognize the data sample provided via a user-friendly interfaces. The data samples involve in this project are data that had been normalize and become the inputs of the prototype. After gathering the data from Hospital Universiti Sains Malaysia, these data samples will be processed through normalization technique in order to extract useful information to make it ready for the training process. Here, backpropagation training algorithm will be used and network parameters will be set. To ensure the performance of the network, its parameter such as momentum value, learning rate and number of hidden neuron will be adjusted and observed in order to get the best weight for the network and enable it to diagnose the bone tumor types.