TY - JFULL AU - Pei-Ju Chao and Tsair-Fwu Lee and Wei-Luen Huang and Long-Chang Chen and Te-Jen Su and Wen-Ping Chen PY - 2010/10/ TI - Applications of Artificial Neural Network to Building Statistical Models for Qualifying and Indexing Radiation Treatment Plans T2 - International Journal of Biomedical and Biological Engineering SP - 485 EP - 491 VL - 4 SN - 1307-6892 UR - https://publications.waset.org/pdf/2329 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 45, 2010 N2 - The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use. ER -