Modeling and Representation by Graphs of the Reasoning of an Emergency Doctor: Symptom Checker MedVir

摘要

This article deals with the symptom checker MedVir which is modeled on the reasoning of an emergency physician. His reasoning is very particular because he often has no knowledge of the patient and he doesn't have much time to evaluate the situation. He needs to make decisions rapidly based on diagnostic hypotheses and an estimation of the severity of the patient's condition. We present a ten step model of the reasoning of an emergency physician by a four layer network composed with what we call a "neuronal entity" and a question prioritization algorithm which checks the most important questions. This "neuronal entity" generalizes the neuron concept but differs from those usually used in machine learning. Visualization by graphs displays all the characteristics of each neuron and each synapse thickness corresponds to the argumentative strength of a question. Hence, these graphs could be very useful in the training of physicians and health professionals.