Evaluation of a Method to Identify and Categorize Section Headers in Clinical Documents

The SecTag algorithm accurately identified both labeled and unlabeled sections in history and physical documents. This type of algorithm may assist in natural language processing applications, such as clinical decision support systems or competency assessment for medical trainees.