Fuzzy-based framework for diagnosis of acid-base disorders
The main objective of this research is to develop a fuzzy-based framework for diagnosis of different acid-base disorders. There are several acid-base disorders that cause many clinical complications and their proper diagnosis is the only way for their efficient treatment. The common disorders are metabolic acidosis, metabolic alkalosis, non-anion gap acidosis, anion-gap acidosis, acute respiratory alkalosis and chronic respiratory alkalosis. The proposed fuzzy-based framework was used to diagnose all of these disorders using four parameters directly measured in blood: hydrogen-ion concentration (pH), arterial blood carbon dioxide partial pressure (paCO(2)), sodium ions concentration (Na(+)) and chloride ions concentration (Cl(-)) along with 12 features extracted from the directly measured parameters. The validation results showed that the developed framework has an accuracy of 94%, an average sensitivity of 88% and a specificity of 93%. These results imply that the developed fuzzy-based framework is accurate and reliable one and can be used to help clinicians specially the non-expert ones to provide correct and rapid diagnosis of acid-base disorders. (C) 2011 Elsevier Ltd. All rights reserved.
acid-base disorders fuzzy inference system computer diagnosis