Abstract
The paradigm of precision medicine often focuses on novel biomarkers, but other types of data directly applicable to patient care could individualize treatment. The response to a cardiovascular and pulmonary intervention is important to critical care providers because it may determine the need and intensity of organ support. Using patient response to predict benefit (or no effect or harm) from an intervention could streamline care better for common syndromes of critical illness such as shock and ARDS, but the necessary data collection and analysis often are complex. Augmented intelligence technologies could assist with this kind of phenotyping because they can analyze and interpret complex multimodal data. In this narrative review, we summarize how augmented intelligence has been used to phenotype responses to diagnostic and therapeutic interventions in cardiovascular and pulmonary failure. We also discuss opportunities for future research that could make this precision approach useful in the clinical environment.