Indicators of the Course Remote Procedures Correction according to IoMT the Patient State Assessments in Restorative Medicine

Abstract

The process of modeling recovery procedures implemented remotely in a 5G network for IoMT and wireless Wi-Fi devices is considered. Reactions to the dynamics of the state vector of Markov chains, as a consequence of deviations in the parameters of the patient state, were studied. An algorithm that establishes a connection between statistical parameters and the facts of hidden failures of measurements has been studied, and definitions have been formed that are suitable for the formation of productive AI rules for the classification of hidden failures. The suitability of the proposed AI tools: the input and output vector of the state, their relative increments, and the assessment of the weight coefficient between the two steps to be information signals of changes in the patient's state was quantitatively investigated. It has been demonstrated that the ratio of the relative changes of the output vector to the relative changes of the input vector is the most sensitive and can serve as a signal indicator of the need for changes in procedures.