A fuzzy logic based Multi-criteria Group Decision Making system for the assesement of umbilical cord acid-base balance

An interpretation of the state of health of the baby can be inferred through assessment of the umbilical cord acid-base (UAB) status. This assessment can be made based on pH and other parameters from both arterial and venous blood from the newborn umbilical cord. This can distinguish the cause of a low pH between the distinct physiological conditions of respiratory acidosis due to a short-term accumulation of CO₂ and a metabolic acidosis (low pH in the tissues) due to lactic acid from a longer-term oxygen deficiency. This UAB assessment suffers the problem of high uncertainty levels between the various experts. Hence, researchers have tried to develop computer based models for the assessment of UAB. Previous research has shown the power of fuzzy logic systems to provide frameworks to handle the encountered uncertainties in real decision making models. Fuzzy Multi-criteria Group Decision Making (MCGDM) has been shown to be an efficient technique for obtaining rankings from experts´ opinions. This paper presents a fuzzy logic based multi-criteria group decision making system for the assessment of umbilical cord acid-base. The proposed system models the variation in the decision making process exhibited by the various experts. We will present results which show how the proposed system can give a better agreement with the experts compared to an existing fuzzy expert system (FES).