A neural network approach for symbolic interpretation in critical care

In this paper, the authors present a work-in-process neural model trained to symbolically characterize the numeric parameters of critical patients in Intensive Care Units (ICUs). The nets were designed to assign the state {very high, high, normal, low, very low} of the main haemodinamic and respiratory parameters based on the particular context of the patient. This symbolic processing allows the use of an heuristic, general module, which prescribes ventilation and oxygenation therapies and shows the diagnoses corresponding to the symbolic labels of those variables.