Natural language processing and machine learning to enable automatic extraction and classification of patients’ smoking status from electronic medical records

摘要

The electronic medical record (EMR) offers unique possibilities for clinical research, but some important patient attributes are not readily available due to its unstructured properties. We applied text mining using machine learning to enable automatic classification of unstructured information on smoking status from Swedish EMR data.