Interpretation of the impact parameter of acid-base status and electrolytes in blood gas analysis in the pulmonary system using artificial intelligence techniques

摘要

During the evaluation of critically ill patients, the status of gases and electrolytes in the blood plays a key role. Therefore, it is often useful to have accessible guidance that would help in certain parts of the evaluation process of types of disorders of acid-base status and electrolyte levels. An expert model of gases and electrolytes in the blood is developed, which generates a diagnosis of any disorder in blood gases and electrolytes using the techniques of artificial intelligence, fuzzy logic, neural networks and hybrid systems based on neuro-fuzzy modeling. After investigating the problem, the relevant parameters are established to establish a diagnosis of disorders as well finding their relationships. The developed expert system with sufficient accuracy determines the type of acid-base disorders and electrolyte abnormalities and their interconnections, depending on the value of anion gaps.