@article{(Open Science Index):https://publications.waset.org/pdf/2329,
	  title     = {Applications of Artificial Neural Network to Building Statistical Models for Qualifying and Indexing Radiation Treatment Plans},
	  author    = {Pei-Ju Chao and  Tsair-Fwu Lee and  Wei-Luen Huang and  Long-Chang Chen and  Te-Jen Su and  Wen-Ping Chen},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Biomedical and Biological Engineering},
	  volume    = {4},
	  number    = {9},
	  year      = {2010},
	  pages     = {486 - 491},
	  ee        = {https://publications.waset.org/pdf/2329},
	  url   	= {https://publications.waset.org/vol/45},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 45, 2010},
	}