Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing

The manual adjudication of disease classification is time-consuming, error-prone, and limits scaling to large datasets. In ischemic stroke (IS), subtype classification is critical for management and outcome prediction. This study sought to use natural language processing of electronic health records (EHR) combined with machine learning methods to automate IS subtyping.Among IS patients from an observational registry with TOAST subtyping...