Fast Neural Networks Decision Algorithm for Pre-Hospital Trauma Care

Science Quest, Incorporated (SQI) proposes to develop an innovative Trauma Care Decision System which will considerably enhance efficiency of pre-hospital trauma care. The system will be capable of accepting multiple sensors data, and provide fast decision, identify high risk patients, estimate patients' survival time and identify the most efficient treatment. The decision algorithms will be based on the use of neural assemblies and bi-radial bases neural networks. In SQI methodology, identification of high risk patients and predication of their survival time is reduced to prediction of the values of the danger functions, which characterize the patients' conditions and their survival time. Developed software will be integrated in hand-held personal computer and adapted for multiple medical sensors logging. The decision making algorithm will be capable to accept data from pH tissue analysis, oxygen tissue analysis, cardiac analysis, and other sensors and will be capable to work with different combinations of input parameters without redesigning the algorithm and retraining the neural network. The set of sensors providing input data for decision making algorithm will be integrated in Pre-Hospital Trauma Care Management Networks.