Computer ontology for an anesthesiology clinical decision-making support system.

<jats:p>Digital transformation of clinical decision-making support processes in anesthesiology is a current and contemporary trend in the development of information technology in healthcare. The implementation of Artificial Intelligence in this area faces certain challenges related to the opacity of the logic behind automated decision-making and low trust in the inference results. To address this issue, computer ontology of an anesthesiologist is proposed as an Artificial Intelligence implementation. Purpose. The aim of the study was to develop a knowledge base in the form of computer ontology for the implementation of an intelligent decision-making support system for anesthesiologists. Materials and methods. A formal logical knowledge base model for an anesthesiologist’s decision-making support system, based on graph theory and semantic networks, is constructed and proposed. Re s u l t s . The proposed model is implemented as an Artificial Intelligence element in a decision-making support system for anesthesiologists, designed to analyze patient data in real time, predict risks, and optimize drug administration during surgery. Findings. The implementation of a decision-making support system for anesthesiologists and resuscitators with elements of artificial intelligence has enabled certain advantages in the digital transformation of anesthesiology procedures, thereby reducing the influence of the human factor in medical decision-making, ensuring patient safety, and optimizing perioperative care.</jats:p>