Systems and methods for converting data associated with a clinical digital artifact to one or more machine learning-informed electronic communications

Abstract

A computer-implemented method for electronic record classification and machine learning inference(s)-informed automated electronic communication includes obtaining one or more electronic records comprising an unstructured component, the unstructured component comprising a textual representation of a set of instructions; extracting a first set of feature vectors comprising features related to a proposed action instruction, and a second set of feature vectors comprising features related to a proposed temporal instruction; computing a first classification inference and a second classification inference that indicates a likely proposed action instruction type and a likely proposed temporal instruction; generating, by the one or more computer processors, a structured digital artifact accessible via a graphical user interface.