Machine Learning (ML) for Enhanced Diagnostic Error Detection and ML Classification of Protein Electrophoresis Text

Researchers are performing chart review to collect true/false positive annotations and construct a vector embedding of patient records, followed by similarity-based retrieval of unlabeled records "near" the labeled ones (semi-supervised approach). The aim is to use machine learning as a filter, after the rules-based retrieval, to improve specificity. Embedding inputs will be selected high-value structured data pertinent to stroke risk and possibly selected prior text notes.