Abstract
This article presents a clinical decision support system for diagnosing acid–base balance disorders based on arterial blood gas (ABG) analysis using the Henderson–Hasselbalch equation. Considering the increasing requirements for accuracy and rapid clinical diagnostics, algorithm-based interpretation of ABG parameters has become highly relevant. The study aims to systematize the key blood gas indicators (рН, 𝑃 𝑎 𝐶𝑂 2 , 𝐻𝐶𝑂 3 − , BE) and analyze their physiological relationships, as well as to develop a logical and mathematical model for automated classification of acid–base disorders. The proposed algorithm enables the identification of metabolic, respiratory, and mixed disturbances, taking compensatory mechanisms into account. The results demonstrate that the implementation of a computerized decision support model enhances diagnostic objectivity, reduces interpretation errors, and improves the quality of clinical decision-making.