SYSTEMS AND METHODS OF CREATING, TRAINING, AND DEPLOYING AN AI-BASED ADVERSE EVENT PREDICTION MODEL AND PLATFORM

Abstract

Methods and systems of creating artificial intelligence processes for predicting adverse events in a patient are provided in which processed vital signs medical data are extracted from a server in communication with one or more vital signs monitors, and raw non-vital signs medical data are extracted from one or more medical instruments, including extracting auxiliary medical data which are not displayed by the medical instruments. The processed vital signs medical data and raw non-vital signs medical data are sent to a cloud-based artificial intelligence platform, which inputs the combined medical data into an AI-driven adverse event prediction model. The adverse event prediction model is continually and automatically fed the combined medical data. The adverse event prediction model identifies adverse event precursors and provides an assessment of a level of risk that a patient will experience an adverse event and a timeframe within which the adverse event is likely to occur.

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