Hybrid expert system in anesthesiology for critical patients

The results achieved using neural networks to represent anesthesiological knowledge specifically in the treatment of patients considered critical from an anesthesiological point of view are shown. This was accomplished using a hybrid expert system applied to anesthesiology, called PROVANES (Proposal and Evaluating of Anesthesia Plan), expanded to cases of critical patients. Its main knowledge base is formed by ten artificial neural networks that perform the tasks involved in an anesthesia plan in the same way as a specialist would do. These nets are embedded in an expert system shell, driven by production rules. This approach bypasses the knowledge elucidation bottleneck to take advantage of the neural net´s knowledge extraction capability