Automated medical chart review for breast cancer outcomes research: a novel natural language processing extraction system.

ABSTRACT:

Background

Manually extracted data points from health records are collated on an institutional, provincial, and national level to facilitate clinical research. However, the labour-intensive clinical chart review process puts an increasing burden on healthcare system budgets. Therefore, an automated information extraction system is needed to ensure the timeliness and scalability of research data.

Methods

We used a dataset of 100 synoptic operative and 100 pathology reports, evenly split into 50 reports in training and test sets for each report type. The training set guided our development of a Natural Language Processing (NLP) extraction pipeline system, which accepts scanned images of operative and pathology reports. The system uses a combination of rule-based and transfer l

SUBMITTER: Chen Y 

PROVIDER: S-EPMC9101856 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature