An accessible, efficient, and accurate natural language processing method for extracting diagnostic data from pathology reports.

ABSTRACT:

Context

Analysis of diagnostic information in pathology reports for the purposes of clinical or translational research and quality assessment/control often requires manual data extraction, which can be laborious, time-consuming, and subject to mistakes.

Objective

We sought to develop, employ, and evaluate a simple, dictionary- and rule-based natural language processing (NLP) algorithm for generating searchable information on various types of parameters from diverse surgical pathology reports.

Design

Data were exported from the pathology laboratory information system (LIS) into extensible markup language (XML) documents, which were parsed by NLP-based Python code into desired data points and delivered to Excel spreadsheets. Accuracy and efficiency were compared to a ma

SUBMITTER: Lam H 

PROVIDER: S-EPMC9808011 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature