Manuscript: Identifying primary and recurrent cancers using a SAS-based natural language processing algorithm
Abstract
Objective Significant limitations exist in the timely and complete identification of primary and recurrent cancers for clinical and epidemiologic research. A SAS-based coding, extraction, and nomenclature tool (SCENT) was developed to address this problem.
Materials and methods SCENT employs hierarchical classification rules to identify and extract information from electronic pathology reports. Reports are