PREDICTION OF ANESTHETIC HAZARDS IN ANIMALS USING ARTIFICIAL INTELLIGENCE ALGORITHMS BASED ON CONTINUOUS MONITORING OF PHYSIOLOGICAL PARAMETERS

Mushinskaya Valeria Anatolyevna  -  student of the veterinary faculty, Autonomous Non-Commercial Organization of Higher Education " Medical Institute named by M.S. Zernov ", Faculty of Veterinary Medicine, Sochi, Russia, 354000, Krasnodar region, Sochi, Parkovaya st., 17,

Kondratenko Elena Igorevna  -  doctor of biological sciences, professor, Associate Professor of Human and Animal Anatomy and Physiology, Professor in the Department of Molecular Biology, Genetics, and Biochemistry, Autonomous Non-Commercial Organization of Higher Education " Medical Institute named by M.S. Zernov", Russia, 354000, Krasnodar region, Sochi, Parkovaya st., 17, condr70@mail.ru

The application of artificial intelligence algorithms for predicting anesthetic risks in animals based on continuous vital sign monitoring. The proposed approach allows for the detection of early signs of hemodynamic and respiratory instability, which contributes to timely correction of anesthetic management and reduction of perioperative and intraoperative mortality.

Key words: artificial intelligence, risk prediction, anesthesiology, monitoring, anesthesia correction, mortality reduction