Using SNOMED CT for High Precision Entity Recognition in Swedish Clinical text

Abstract

An evaluation was performed of retrieval of findings in Swedish clinical text through exact string matching against SNOMED CT. The aim was to create a system for retrieving clinical findings with high precision that for example can be used as training data for machine learning. The evaluation was performed on previously manually annotated findings, and the best approach showed a precision of 93 percent