USING NEURAL NETWORKS FOR TRAUMA OUTCOME EVALUATION

The development of effective methods for predicting the survival or mo rtality of patients is a major focus of trauma research. We address th is problem by applying neural network modelling, using as inputs estab lished descriptors of physiologic and anatomic injury severity, We use two different ''backpropagation'' techniques with a variety of traini ng strategies and examine the importance of training and test set comp osition, performance evaluation criteria, and interpretation of networ k outputs, The results of our study indicate that neural networks show significant promise for trauma patient outcome evaluation.