Fast Neural Networks Decision Algorithm for Pre-Hospital Trauma Care. Phase I
Abstract
In response to DOD Army solicitation A95-095, SQI proposed a new type of Trauma Care Decision System considerably enhancing efficiency of prehospital trauma care. The greatest advantage of SQI's triage support system is the capability of accepting multiple sensors data, and provide fast decision, identify high risk patients, estimate patients' survival time and identify the most efficient and effective treatment. The decision algorithms is based on the use of neural assemblies and SQI's proprietary bi-radial bases neural networks. In SQI methodology, identification of high risk patients and prediction of their survival time is reduced to prediction of the values of the danger functions, which characterize the patients' conditions and their survival time. The preliminary prototype software was integrated in hand-held personal computer from Texas Microsystems Inc., and adapted for multiple medical sensors logging. The decision making algorithm is 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. This SQI developed preliminary algorithm has high potential greatly enhance the Army's Casualties Life Support during Trauma and Transport.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1996
- Accession Number
- ADB216715
Entities
People
- Simon Katz