Neural Network Medical Decision Algorithms for Pre-Hospital Trauma Care. Phase 1
Final rept. 15 Mar 1996-14 Sep 1996
BARRON ASSOCIATES INC CHARLOTTESVILLE VA
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This SBIR Phase I research project is concerned with the problem of civilian and military trauma management, whose paramount issues include 1 obtaining knowledge about the physiological condition of the injured patient e.g., injury severity assessment and survival likelihood prediction and 2 making intelligent use of that information for pragmatic decisional purposes e.g., triage. The emphasis of our research effort is on assessing the ability of polynomial neural network PNN methods to improve on conventional trauma scoring systems and other modeling approaches, such as logistic regression. Using several real-world civilian trauma registry databases, we demonstrated 1 that PNN models can provide significant improvement over existing pre-hospital and ex post scoring systems, such as T-RTS, TRISS, and ASCOT, in terms of the specificity-sensitivity characteristics of mortality prediction 2 the ability to discriminate accurately among three or more classes of patients e.g., RSD, AMBER, and GREEN triage categories 3 the ability to compensate for missing input variables while achieving results not significantly different from those obtained using models that did not rely on such inputs and 4 the ability to obtain superior performance through time-series modeling of available patient data.
- Anatomy and Physiology
- Medicine and Medical Research