Abstract

This paper describes  a  decision support system aiming to assist clinicians in assessing acid-base metabolic disorders. The system is computing acid-base derived parameters from Astrup data. The inference mechanism, based on a binary decision tree classifies the disturbance in one of twelve classes. Finally, a suggested therapy is derived. The system is designed to be used in a clinical environment by medical staff and provides a quick, accurate and informed advice.

Keywords

Expert systems, Acid-base metabolic disorders.